There are 4 repositories under disentanglement topic.
Experiments for understanding disentanglement in VAE latent representations
A curated list of awesome work on VAEs, disentanglement, representation learning, and generative models.
Dataset to assess the disentanglement properties of unsupervised learning methods
Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation :star2:
Replicating "Understanding disentangling in Ξ²-VAE"
π§Ά Modular VAE disentanglement framework for python built with PyTorch Lightning βΈ Including metrics and datasets βΈ With strongly supervised, weakly supervised and unsupervised methods βΈ Easily configured and run with Hydra config βΈ Inspired by disentanglement_lib
Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.
[CVPR2020] Hi-CMD: Hierarchical Cross-Modality Disentanglement for Visible-Infrared Person Re-Identification
Pytorch implementation of Learning Disentangled Representations via Mutual Information Estimation (ECCV 2020)
The official implementation of "Disentangling Long and Short-Term Interests for Recommendation" (WWW '22)
Orthogonal Jacobian Regularization for Unsupervised Disentanglement in Image Generation (ICCV 2021)
Implementation of "Disentangled Representation Learning for Non-Parallel Text Style Transfer(ACL 2019)" in Pytorch
This repository summarizes the material gathered for the tutorial on learning disentangled representations in the imaging domain, and serves as a roadmap for the disentanglement aficionados.
Dataset and model for disentangling chat on IRC
Library implementing state-of-the-art Concept-based and Disentanglement Learning methods for Explainable AI
Official pytorch implementation of "Scaling-up Disentanglement for Image Translation", ICCV 2021.
[ICML 2020] InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs
Official code for Interspeech 2023 paper "Self-supervised Fine-tuning for Improved Content Representations by Speaker-invariant Clustering"
Official implementation of the paper *PDE-Driven Spatiotemporal Disentanglement*
Dataset to study disentanglement in the context of symbolic music. Published as an ISMIR'20 paper titled: "dMelodies: A Music Dataset for Disentanglement Learning"
Official pytorch implementation of "An Image is Worth More Than a Thousand Words: Towards Disentanglement in the Wild", NeurIPS 2021.
Code from the article: "The Role of Disentanglement in Generalisation" (ICLR, 2021).
This is the code for the paper Embrace the Gap: VAEs perform Independent Mechanism Analysis, showing that optimizing the ELBO is equivalent to optimizing the IMA-regularized log-likelihood under certain assumptions (e.g., small decoder variance).
[TPAMI 2023] Code for inference of our TPAMI and ECCV papers on model-guided disentanglement for GANs.
Official implementation for KDD'22 paper "Learning Fair Representation via Distributional Contrastive Disentanglement"
Matching in GAN latent space for better bias benchmarking and semantic image editing. πΆπ»π§πΎπ©πΌβπ¦°π±π½ββοΈπ΄πΎ
Official code of "Discover the Unknown Biased Attribute of an Image Classifier" (ICCV 2021)
A curated list of papers on disentangled representation learning inspired by https://github.com/sootlasten/disentangled-representation-papers and https://github.com/matthewvowels1/Awesome-VAEs.
Codebase for the paper: Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts
PyTorch Implementation for the paper "DisCont: Self-Supervised Visual Attribute Disentanglement using Context Vectors" (ECCVW'20).
Official pytorch re-implementation of "Demystifying Inter-Class Disentanglement", ICLR 2020.
An Image Dataset for Causal Analysis in Disentangled Representations