[ECCV 2024] The official repo for "SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders"
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Updated
Jul 12, 2024 - Python
[ECCV 2024] The official repo for "SA-DVAE: Improving Zero-Shot Skeleton-Based Action Recognition by Disentangled Variational Autoencoders"
Code for "Predicting Cellular Responses to Novel Drug Perturbations at a Single-Cell Resolution", NeurIPS 2022.
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).
Learning alternative disentangled representations using weak labels
Single-Cell (Perturbation) Model Library
Pytorch implementation of Semi-Supervised Disentanglement of Class-Related and Class-Independent Factors in VAE paper
Codebase for the paper: Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts
Learning Face Recognition Unsupervisedly by Disentanglement and Self-Augmentation (ICRA 2020)
Dataset and model for disentangling chat on IRC
Object-Centric Disentangled Mechanisms
Implementation of "Disentangled Representation Learning for Non-Parallel Text Style Transfer(ACL 2019)" in Pytorch
Official code for Interspeech 2023 paper "Self-supervised Fine-tuning for Improved Content Representations by Speaker-invariant Clustering"
Time-Lapse Disentanglement With Conditional GANs [SIGGRAPH 2022]
[TPAMI 2023] Code for inference of our TPAMI and ECCV papers on model-guided disentanglement for GANs.
Matching in GAN latent space for better bias benchmarking and semantic image editing. 👶🏻🧒🏾👩🏼🦰👱🏽♂️👴🏾
🧶 Modular VAE disentanglement framework for python built with PyTorch Lightning ▸ Including metrics and datasets ▸ With strongly supervised, weakly supervised and unsupervised methods ▸ Easily configured and run with Hydra config ▸ Inspired by disentanglement_lib
Experiments for understanding disentanglement in VAE latent representations
This is the code repository for {Empirical Study on Exploring the Impact of Controlling the Objective on Disentanglement Learning During Training}.
Official implementation of the paper "Learning Invariance Manifolds of Visual Sensory Neurons".
Official pytorch implementation of "An Image is Worth More Than a Thousand Words: Towards Disentanglement in the Wild", NeurIPS 2021.
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