\begin{table*}[t]
\vspace{-0.1in}
\caption{Few-shot graph classification results. The best results are highlighted in bold while the best baseline results are underlined. -I and -T denote inductive and transductive settings of CGFL, respectively. Teacher indicates the CGFL model without knowledge distillation.}
\vspace{-0.1in}
\label{tab:graph-cls-1}
\centering
\resizebox{1\textwidth}{!}{
\begin{tabular} {c|cc|cc|cc|cc}
\toprule
\multirow{2}{*}{Method} & \multicolumn{2}{c|}{Letter-High} &\multicolumn{2}{c|}{Triangles} &\multicolumn{2}{c|}{Reddit-12K} &\multicolumn{2}{c}{Enzymes}  \\ 
\cmidrule{2-9}
& 5-shot & 10-shot & 5-shot & 10-shot & 5-shot & 10-shot & 5-shot & 10-shot  \\
\midrule
WL &65.27$\pm$7.67&68.39$\pm$4.69  &51.25$\pm$4.02&53.26$\pm$2.95 &40.26$\pm$5.17 &42.57$\pm$3.69 &55.78$\pm$4.72 &58.47$\pm$3.84  \\ 
Graphlet &33.76$\pm$6.94&37.59$\pm$4.60  &40.17$\pm$3.18&43.76$\pm$3.09 &33.76$\pm$6.94 &37.59$\pm$4.60 &53.17$\pm$5.92 &55.30$\pm$3.78  \\ 
AWE &40.60$\pm$3.91&42.20$\pm$2.87  &39.36$\pm$3.85&42.58$\pm$3.11 &30.24$\pm$2.34 &33.44$\pm$2.04 &43.75$\pm$1.85 &45.58$\pm$2.11\\ 
Graph2Vec  &66.12$\pm$5.21&68.17$\pm$4.26  &48.38$\pm$3.85&50.16$\pm$4.15 &27.85$\pm$4.21 &29.97$\pm$3.17 &55.88$\pm$4.86 &58.22$\pm$4.30  \\ 
Diffpool  &58.69$\pm$6.39&61.59$\pm$5.21 &64.17$\pm$5.87&67.12$\pm$4.29 &35.24$\pm$5.69 &37.43$\pm$3.94 &45.64$\pm$4.56 &49.64$\pm$4.23 \\ 
CapsGNN  &56.60$\pm$7.86&60.67$\pm$5.24 &65.40$\pm$6.13&68.37$\pm$3.67 &36.58$\pm$4.28 &39.16$\pm$3.73 &52.67$\pm$5.51 &55.31$\pm$4.23  \\ 
GIN &65.83$\pm$7.17&69.16$\pm$5.14 &63.80$\pm$5.61&67.30$\pm$4.35 &40.36$\pm$4.69 &43.70$\pm$3.98 &55.73$\pm$5.80 &58.83$\pm$5.32 \\ 
GIN-KNN &63.52$\pm$7.27&65.66$\pm$8.69 &58.34$\pm$3.91&61.55$\pm$3.19 &41.31$\pm$2.84 &43.58$\pm$2.80 &57.24$\pm$7.06 &59.34$\pm$5.24 \\ 
GSM-GCN &68.69$\pm$6.50&72.80$\pm$4.12 &69.37$\pm$4.92&73.11$\pm$3.94 &40.77$\pm$4.32 &44.28$\pm$3.86 &54.34$\pm$5.64 &58.16$\pm$4.39 \\ 
GSM-GAT &69.91$\pm$5.90&\underline{73.28$\pm$3.46} &71.40$\pm$4.34 &\underline{75.60$\pm$3.67} &41.59$\pm$4.12 &\underline{45.67$\pm$3.68} &55.42$\pm$5.74 &60.64$\pm$3.84 \\ 
AS-MAML &\underline{70.23$\pm$1.53} &73.19$\pm$1.17 &\underline{71.56$\pm$1.17} &75.56$\pm$2.39 &\underline{41.90$\pm$1.65} &45.66$\pm$1.11 &\underline{56.03$\pm$1.85} &\underline{60.79$\pm$2.74} \\ 
\midrule
Teacher-I &{71.43$\pm$5.23} &{73.62$\pm$2.93}  &{71.93$\pm$3.51} &{76.21$\pm$2.87} &{42.32$\pm$4.48} &{46.31$\pm$3.84}  &{57.53$\pm$3.16} &{61.12$\pm$4.80} \\
CGFL-I &{72.12$\pm$4.88} &{74.08$\pm$3.30} &{72.34$\pm$3.42} &{76.91$\pm$2.98} &{42.85$\pm$4.62} &{46.89$\pm$4.96} &{57.94$\pm$2.85} &{61.66$\pm$4.61}\\
Teacher-T &{75.20$\pm$4.34} &{78.35$\pm$1.95}   &{78.55$\pm$3.75} &{81.03$\pm$3.37} &{44.80$\pm$4.85} &{48.95$\pm$4.03}  &{59.85$\pm$2.34} &{62.30$\pm$3.29}  \\
CGFL-T &\textbf{75.97$\pm$5.02} &\textbf{79.10$\pm$4.23}  &\textbf{79.32$\pm$4.05} &\textbf{81.78$\pm$3.30} &\textbf{45.55$\pm$3.67} &\textbf{49.32$\pm$4.21} &\textbf{60.34$\pm$4.04} &\textbf{62.97$\pm$2.92}  \\
\midrule
\end{tabular}}
\vspace{-0.2in}
\end{table*}
\textbf{GFL Setting and Problem}. Let $\mathcal{C}_{base}$ and $\mathcal{C}_{novel}$ denote the base classes set and novel (new) classes set in training data $\mathcal{T}_{train}$ and testing data $\mathcal{T}_{test}$, respectively. 
Similar to the general meta-learning problem~\cite{finn2017model}, the purpose of graph few-shot learning (GFL) is to train a GNN encoder $f_\theta(\cdot)$ over $\mathcal{C}_{base}$, such that the trained GNN encoder can be quickly adapted to $\mathcal{C}_{novel}$ with few labels per class. Note that there is no overlapping between base classes and novel classes, i.e., $\mathcal{C}_{base} \cap \mathcal{C}_{novel} = \emptyset$. 
In $K$-shot setting, during the meta-training phase,
a batch of classes (tasks) is randomly sampled from $\mathcal{C}_{base}$, where $K$ labeled instances per class are sampled to form the support set $\mathcal{S}$ for model training and the remaining instances are taken as the query set $\mathcal{Q}$ for model evaluation. After sufficient training, the model is further transferred to the meta-testing phase to conduct $N$-way classification over $\mathcal{C}_{novel}$ ($N$ is the number of novel classes), where each class is only with $K$ labeled instances. GFL applies to different graph mining problems, depending on the class meaning. Each class corresponds to a node label for the node classification problem or corresponds to a graph label for the graph classification problem. In this work, we will study both node classification and graph classification problems under few-shot setting, which are formally defined as follows:

\subsection{Self-Distilled Graph Contrastive Learning}
\textbf{GNN Contrastive Pre-training}. In the first phase, we firstly introduce contrastive learning to pre-train GNN. Inspired by the representation bootstrapping technique~\cite{grill2020bootstrap}, our method learns node (or graph) representation by discriminating context instances. Specifically, two GNN encoders: an online GNN $f_\theta(\cdot)$ and a target GNN $f_\xi(\cdot)$, are introduced to encode two randomly augmented views of a given graph. The online GNN is supervised under the target GNN's output, while the target GNN is updated by the online GNN's exponential moving average. The contrastive pre-training step is shown in Figure~\ref{fig:ssl}(a).
\\
\textit{Graph Augmentation:} The given graph $G$ is processed with randomly data augmentations to generate a contrastive pair ($G^{\prime}$, $G^{\prime\prime}$) as the input for two GNN branches (online branch and target branch) of the following GNN training. In this work, we apply a combination of stochastic node feature masking, edge removing, and node dropping with constant probabilities for graph augmentation.
\\
\textit{GNN Update:} With the generated graph pair ($G^{\prime}$, $G^{\prime\prime}$), the online GNN $f_\theta(\cdot)$ and the target GNN $f_\xi(\cdot)$ are respectively utilized to process $G^{\prime}$ and $G^{\prime\prime}$ for node (or graph) embeddings generation. Both GNNs have the same architecture, while a two-layer FC (one-layer FC) is attached after online GNN (target GNN) to refine embedding. The reason that two branches have different FC layers is to prevent the prediction of the online model from being exactly the same as the output of the target model, thus avoiding the learned representation collapse. Later, to enforce online GNN's embeddings $z_\theta$ approximate the target GNN's embeddings $h_\xi$, the mean squared error between them is formulated as the objective function:

where $\tau \in [0, 1]$ is the decay rate. Note that the target GNN stops the backpropagation from $\mathcal{L}_{\theta,\xi}$, and it is only updated by EMA.
\textbf{Contrastive Distillation}.
With the pre-trained GNN $f_\theta(\cdot)$ obtained in the previous step, we introduce a self-distillation step to elevate $f_\theta(\cdot)$. This is inspired by the Born-again strategy~\cite{furlanello2018born}, which implies a well-trained teacher can boost a random initialized identical student. The distillation step adopts a similar contrastive framework as the previous step, as shown in Figure~\ref{fig:ssl}(a). Specifically, we load the pre-trained GNN $f_\theta(\cdot)$ and take it as the teacher model $f_{\theta_{t}}(\cdot)$. The teacher model is frozen and applied to distill a student model $f_{\theta_{s}}(\cdot)$.
Two augmented views ($G^{*}$, $G^{**}$) of a graph $G$ are generated and fed to $f_{\theta_{t}}(\cdot)$ and $f_{\theta_{s}}(\cdot)$, respectively. Later,
the student's normalized output is forced to approximate the teacher's normalized output as follows:

where $\alpha$ is the learning step size, $\mathcal{L}^{\mathcal{S}_{i}}_{\mathcal{T}_i}$ denotes the downstream task loss over $\mathcal{S}_{i}$. In this work, we employ prototypical loss~\cite{snell2017prototypical} for node or graph classification, which uses embeddings extracted from the support set by a neural network as the class prototype, and the query set is classified according to the distance between its embeddings and prototypes. The task-specific parameter $\theta_{{s, i}}'$ is further utilized to compute the loss over query set $\mathcal{Q}_{i}$ of $T_i$: $\mathcal{L}^{\mathcal{Q}_{i}}_{\mathcal{T}_i}(f_{\theta_{{s, i}}'})$. Later, $\mathcal{L}^{\mathcal{Q}_{i}}_{\mathcal{T}_i}(f_{\theta_{{s, i}}'})$ of a batch of randomly sampled tasks are summed up to update the model parameters $\theta_{s}$ (i.e., outer-loop):

where $x_{i}$ denotes a random variable of $i$-th node attribute in the graph. 
Then, we introduce a  noise perturbation-based method to approximate $H(x_{i}|{\bf {z}})$. Specifically,  let $\widetilde{x_i}=x_i+{\bf \epsilon}_i$ (${\bf \epsilon}_i \sim \mathcal{N}(0, {\bf \Sigma}_i={\bf \sigma}^2_i{\bf I})$) and we aim to optimize the following loss function:

where $\bm{\sigma}$ = $[\sigma_1, \sigma_2, \cdots, \sigma_n]$ are learnable parameters; 
$\beta$ is trade-off weight. In particular, the first term of the above objective minimizes difference between the encoded embedding of noisy input and the hidden state while the second term encourages a high conditional entropy according to the maximum entropy principle. In this way, we have $p(\widetilde{x_i}|{\bf z})=p({\bf \epsilon}_i)$ and $H(x_i|{\bf z})$ is approximated by $H(\widetilde{x}_i|{\bf z})$:

where $C = \frac{1}{2}\log (2\pi e)$. By taking Eqn.~\ref{eq:infoloss-7} into Eqn.~\ref{eq:infoloss-6}, 
we can optimize $\mathcal{L}(\bm{\sigma})$ with Adam optimizer and obtain the optimal $\bm{\sigma}$ for computing the overall discarded information $H(G|Z)$. Furthermore, we can explain GFL model's capability by comparing discarded information of different models. Ideally, we expect the GFL model to encode valid node (or graph) embeddings as much as possible and therefore discard information as small as possible. 

\vspace{-0.15in}
\subsection{Few-Shot Graph Classification}
\vspace{-0.1in}
\textbf{Overall Performance}.
The results of all models for 5/10-shot graph classification
are reported in Table~\ref{tab:graph-cls-1}. Similar to the findings obtained from Table~\ref{tab:node-cls-1}, according to this table: (1) CGFL outperforms all baseline models, showing its superiority for few-shot graph classification;
(2) The improvement of CGFL-I over baseline models ranges from 0.95\% to 38.36\% (5-shot) and from 0.8\% to 34.33\% (10-shot). Meanwhile, this value of CGFL-T ranges from 5.65\% to 46.21\% (5-shot) and from 2.18\% to 41.51\% (10-shot). This demonstrates the effect of contrastive pre-training and self-distillation in learning rich graph embedding from unlabeled data; (3) CGFL-T (or Teacher-T) outperforms CGFL-I (or Teacher-I), showing that unlabeled data in testing set improves model's generalization; {(4) CGFL is better than teacher model as contrastive distillation step further elevates the model.}
{"value": "65.27", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "WL", "model settings": {"xx": "yy"}} {"value": "68.39", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "WL", "model settings": {"xx": "yy"}} {"value": "51.25", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "WL", "model settings": {"xx": "yy"}} {"value": "53.26", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "WL", "model settings": {"xx": "yy"}} {"value": "40.26", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "WL", "model settings": {"xx": "yy"}} {"value": "42.57", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "WL", "model settings": {"xx": "yy"}} {"value": "55.78", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "WL", "model settings": {"xx": "yy"}} {"value": "58.47", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "WL", "model settings": {"xx": "yy"}} {"value": "33.76", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "Graphlet", "model settings": {"xx": "yy"}} {"value": "37.59", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "Graphlet", "model settings": {"xx": "yy"}} {"value": "40.17", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "Graphlet", "model settings": {"xx": "yy"}} {"value": "43.76", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "Graphlet", "model settings": {"xx": "yy"}} {"value": "33.76", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "Graphlet", "model settings": {"xx": "yy"}} {"value": "37.59", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "Graphlet", "model settings": {"xx": "yy"}} {"value": "53.17", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "Graphlet", "model settings": {"xx": "yy"}} {"value": "55.30", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "Graphlet", "model settings": {"xx": "yy"}} {"value": "40.60", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "AWE", "model settings": {"xx": "yy"}} {"value": "42.20", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "AWE", "model settings": {"xx": "yy"}} {"value": "39.36", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "AWE", "model settings": {"xx": "yy"}} {"value": "42.58", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "AWE", "model settings": {"xx": "yy"}} {"value": "30.24", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "AWE", "model settings": {"xx": "yy"}} {"value": "33.44", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "AWE", "model settings": {"xx": "yy"}} {"value": "43.75", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "AWE", "model settings": {"xx": "yy"}} {"value": "45.58", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "AWE", "model settings": {"xx": "yy"}} {"value": "66.12", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "Graph2Vec", "model settings": {"xx": "yy"}} {"value": "68.17", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "Graph2Vec", "model settings": {"xx": "yy"}} {"value": "48.38", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "Graph2Vec", "model settings": {"xx": "yy"}} {"value": "50.16", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "Graph2Vec", "model settings": {"xx": "yy"}} {"value": "27.85", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "Graph2Vec", "model settings": {"xx": "yy"}} {"value": "29.97", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "Graph2Vec", "model settings": {"xx": "yy"}} {"value": "55.88", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "Graph2Vec", "model settings": {"xx": "yy"}} {"value": "58.22", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "Graph2Vec", "model settings": {"xx": "yy"}} {"value": "58.69", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "Diffpool", "model settings": {"xx": "yy"}} {"value": "61.59", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "Diffpool", "model settings": {"xx": "yy"}} {"value": "64.17", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "Diffpool", "model settings": {"xx": "yy"}} {"value": "67.12", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "Diffpool", "model settings": {"xx": "yy"}} {"value": "35.24", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "Diffpool", "model settings": {"xx": "yy"}} {"value": "37.43", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "Diffpool", "model settings": {"xx": "yy"}} {"value": "45.64", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "Diffpool", "model settings": {"xx": "yy"}} {"value": "49.64", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "Diffpool", "model settings": {"xx": "yy"}} {"value": "56.60", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "CapsGNN", "model settings": {"xx": "yy"}} {"value": "60.67", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "CapsGNN", "model settings": {"xx": "yy"}} {"value": "65.40", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "CapsGNN", "model settings": {"xx": "yy"}} {"value": "68.37", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "CapsGNN", "model settings": {"xx": "yy"}} {"value": "36.58", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "CapsGNN", "model settings": {"xx": "yy"}} {"value": "39.16", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "CapsGNN", "model settings": {"xx": "yy"}} {"value": "52.67", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "CapsGNN", "model settings": {"xx": "yy"}} {"value": "55.31", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "CapsGNN", "model settings": {"xx": "yy"}} {"value": "65.83", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "GIN", "model settings": {"xx": "yy"}} {"value": "69.16", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "GIN", "model settings": {"xx": "yy"}} {"value": "63.80", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "GIN", "model settings": {"xx": "yy"}} {"value": "67.30", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "GIN", "model settings": {"xx": "yy"}} {"value": "40.36", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "GIN", "model settings": {"xx": "yy"}} {"value": "43.70", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "GIN", "model settings": {"xx": "yy"}} {"value": "55.73", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "GIN", "model settings": {"xx": "yy"}} {"value": "58.83", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "GIN", "model settings": {"xx": "yy"}} {"value": "63.52", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "GIN-KNN", "model settings": {"xx": "yy"}} {"value": "65.66", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "GIN-KNN", "model settings": {"xx": "yy"}} {"value": "58.34", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "GIN-KNN", "model settings": {"xx": "yy"}} {"value": "61.55", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "GIN-KNN", "model settings": {"xx": "yy"}} {"value": "41.31", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "GIN-KNN", "model settings": {"xx": "yy"}} {"value": "43.58", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "GIN-KNN", "model settings": {"xx": "yy"}} {"value": "57.24", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "GIN-KNN", "model settings": {"xx": "yy"}} {"value": "59.34", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "GIN-KNN", "model settings": {"xx": "yy"}} {"value": "68.69", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "GSM-GCN", "model settings": {"xx": "yy"}} {"value": "72.80", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "GSM-GCN", "model settings": {"xx": "yy"}} {"value": "69.37", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "GSM-GCN", "model settings": {"xx": "yy"}} {"value": "73.11", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "GSM-GCN", "model settings": {"xx": "yy"}} {"value": "40.77", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "GSM-GCN", "model settings": {"xx": "yy"}} {"value": "44.28", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "GSM-GCN", "model settings": {"xx": "yy"}} {"value": "54.34", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "GSM-GCN", "model settings": {"xx": "yy"}} {"value": "58.16", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "GSM-GCN", "model settings": {"xx": "yy"}} {"value": "69.91", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "GSM-GAT", "model settings": {"xx": "yy"}} {"value": "73.28", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "GSM-GAT", "model settings": {"xx": "yy"}} {"value": "71.40", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "GSM-GAT", "model settings": {"xx": "yy"}} {"value": "75.60", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "GSM-GAT", "model settings": {"xx": "yy"}} {"value": "41.59", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "GSM-GAT", "model settings": {"xx": "yy"}} {"value": "45.67", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "GSM-GAT", "model settings": {"xx": "yy"}} {"value": "55.42", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "GSM-GAT", "model settings": {"xx": "yy"}} {"value": "60.64", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "GSM-GAT", "model settings": {"xx": "yy"}} {"value": "70.23", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "AS-MAML", "model settings": {"xx": "yy"}} {"value": "73.19", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "AS-MAML", "model settings": {"xx": "yy"}} {"value": "71.56", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "AS-MAML", "model settings": {"xx": "yy"}} {"value": "75.56", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "AS-MAML", "model settings": {"xx": "yy"}} {"value": "41.90", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "AS-MAML", "model settings": {"xx": "yy"}} {"value": "45.66", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "AS-MAML", "model settings": {"xx": "yy"}} {"value": "56.03", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "AS-MAML", "model settings": {"xx": "yy"}} {"value": "60.79", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "AS-MAML", "model settings": {"xx": "yy"}} {"value": "71.43", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "Teacher-I", "model settings": {"xx": "yy"}} {"value": "73.62", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "Teacher-I", "model settings": {"xx": "yy"}} {"value": "71.93", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "Teacher-I", "model settings": {"xx": "yy"}} {"value": "76.21", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "Teacher-I", "model settings": {"xx": "yy"}} {"value": "42.32", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "Teacher-I", "model settings": {"xx": "yy"}} {"value": "46.31", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "Teacher-I", "model settings": {"xx": "yy"}} {"value": "57.53", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "Teacher-I", "model settings": {"xx": "yy"}} {"value": "61.12", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "Teacher-I", "model settings": {"xx": "yy"}} {"value": "72.12", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "CGFL-I", "model settings": {"xx": "yy"}} {"value": "74.08", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "CGFL-I", "model settings": {"xx": "yy"}} {"value": "72.34", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "CGFL-I", "model settings": {"xx": "yy"}} {"value": "76.91", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "CGFL-I", "model settings": {"xx": "yy"}} {"value": "42.85", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "CGFL-I", "model settings": {"xx": "yy"}} {"value": "46.89", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "CGFL-I", "model settings": {"xx": "yy"}} {"value": "57.94", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "CGFL-I", "model settings": {"xx": "yy"}} {"value": "61.66", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "CGFL-I", "model settings": {"xx": "yy"}} {"value": "75.20", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "Teacher-T", "model settings": {"xx": "yy"}} {"value": "78.35", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "Teacher-T", "model settings": {"xx": "yy"}} {"value": "78.55", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "Teacher-T", "model settings": {"xx": "yy"}} {"value": "81.03", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "Teacher-T", "model settings": {"xx": "yy"}} {"value": "44.80", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "Teacher-T", "model settings": {"xx": "yy"}} {"value": "48.95", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "Teacher-T", "model settings": {"xx": "yy"}} {"value": "59.85", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "Teacher-T", "model settings": {"xx": "yy"}} {"value": "62.30", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "Teacher-T", "model settings": {"xx": "yy"}} {"value": "75.97", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "CGFL-T", "model settings": {"xx": "yy"}} {"value": "79.10", "type": "Result", "training data/set": "Letter-High", "test data/set": "Letter-High", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "CGFL-T", "model settings": {"xx": "yy"}} {"value": "79.32", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "CGFL-T", "model settings": {"xx": "yy"}} {"value": "81.78", "type": "Result", "training data/set": "Triangles", "test data/set": "Triangles", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "CGFL-T", "model settings": {"xx": "yy"}} {"value": "45.55", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "CGFL-T", "model settings": {"xx": "yy"}} {"value": "49.32", "type": "Result", "training data/set": "Reddit-12K", "test data/set": "Reddit-12K", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "CGFL-T", "model settings": {"xx": "yy"}} {"value": "60.34", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"5-shot": "true"}, "model": "CGFL-T", "model settings": {"xx": "yy"}} {"value": "62.97", "type": "Result", "training data/set": "Enzymes", "test data/set": "Enzymes", "task": ["Few-shot graph classification", "graph classification"], "metric": "Accuracy", "experimental settings": {"10-shot": "true"}, "model": "CGFL-T", "model settings": {"xx": "yy"}}