Replicating "Understanding disentangling in β-VAE"
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Updated
Jun 2, 2018 - Python
Replicating "Understanding disentangling in β-VAE"
Correlated Ellipses dataset for measuring disentanglement when the factors of variation are correlated. See our paper "Hyperprior Induced Unsupervised Disentanglement of Latent Representations" (AAAI 2019)
Pytorch implementation of JointVAE, a framework for disentangling continuous and discrete factors of variation 🌟
A toolkit to make working with fd3 easier
Spatial Decomposition and Transformation Network - TensorFlow
Improving Disentangled Representatoin Learning with the Beta Bernoulli Process. ICDM 2019.
Spatial Decomposition Network - TensorFlow
Dataset to study disentanglement in the context of symbolic music. Published as an ISMIR'20 paper titled: "dMelodies: A Music Dataset for Disentanglement Learning"
PyTorch Implementation for the paper "DisCont: Self-Supervised Visual Attribute Disentanglement using Context Vectors" (ECCVW'20).
[ICML 2020] InfoGAN-CR and ModelCentrality: Self-supervised Model Training and Selection for Disentangling GANs
PyTorch version of disentanglement lib
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.
Dataset to assess the disentanglement properties of unsupervised learning methods
Making locally disentangled vaes.
Official implementation of the paper *PDE-Driven Spatiotemporal Disentanglement*
[CVPR2020] Hi-CMD: Hierarchical Cross-Modality Disentanglement for Visible-Infrared Person Re-Identification
Code corresponding to the DiCyR ICLR submission, used for my first research project at ISAE-Supaero.
Code for Benchmarks, Algorithms, and Metrics for Hierarchical Disentanglement
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