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ae_tracerx_2d

transcriptomics
dimensionality-reduction
ae
tracerx
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metadata
title: Autoencoder TRACERx-focused 2D
emoji: 🧬
colorFrom: blue
colorTo: green
sdk: pytorch
tags:
  - transcriptomics
  - dimensionality-reduction
  - ae
  - tracerx
license: mit

Autoencoder (TRACERx-focused, 2D)

This model is part of the TRACERx Datathon 2025 transcriptomics analysis pipeline.

Model Details

  • Model Type: Autoencoder
  • Dataset: TRACERx-focused
  • Latent Dimensions: 2
  • Compression Mode: samples
  • Framework: PyTorch

Usage

This model is designed to be used with the TRACERx Datathon 2025 analysis pipeline. It will be automatically downloaded and cached when needed.

Model Architecture

  • Input: Gene expression data
  • Hidden layers: [input_size, 512, 256, 128, 2]
  • Output: 2-dimensional latent representation
  • Activation: ELU with batch normalization

Training Data

Trained exclusively on TRACERx open dataset

Files

  • autoencoder_2_latent_dims_oos_mode.pt: Main model weights
  • latent_df.csv: Example latent representations (if available)