dcmoyer / invariance-tutorialLinks
A tutorial on learned non-adversarial invariance in neural networks
☆13Updated 5 years ago
Alternatives and similar repositories for invariance-tutorial
Users that are interested in invariance-tutorial are comparing it to the libraries listed below
Sorting:
- This repository contains a pytorch implementation for the paper: Multi-Level Variational Autoencoder (https://arxiv.org/abs/1705.08841), …☆71Updated 3 years ago
- VAEs and nonlinear ICA: a unifying framework☆47Updated 6 years ago
- Official source code repository for the ICML 2021 paper "Hierarchical VAEs Know What They Don't Know"☆30Updated 3 years ago
- Learning Autoencoders with Relational Regularization☆46Updated 4 years ago
- Code for "Generating Interpretable Counterfactual Explanations By Implicit Minimisation of Epistemic and Aleatoric Uncertainties"☆18Updated 4 years ago
- ☆63Updated 4 years ago
- An Empirical Framework for Domain Generalization In Clinical Settings☆31Updated 3 years ago
- Code for Sliced Gromov-Wasserstein☆68Updated 5 years ago
- Code for Invariant Rep. Without Adversaries (NIPS 2018)☆35Updated 5 years ago
- Generalizing to unseen domains via distribution matching☆72Updated 4 years ago
- Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)☆32Updated 3 years ago
- Implementation of 'DIVA: Domain Invariant Variational Autoencoders'☆103Updated 5 years ago
- Code to accompany the paper 'Improving model calibration with accuracy versus uncertainty optimization'.☆54Updated 2 years ago
- PyTorch implementation for the ICLR 2020 paper "Understanding the Limitations of Variational Mutual Information Estimators"☆74Updated 5 years ago
- Contrastive Variational Autoencoders☆69Updated 6 years ago
- ☆37Updated 4 years ago
- Code for "Learning with minibatch Wasserstein: asymptotic and gradient properties".☆13Updated 4 years ago
- ☆46Updated 4 years ago
- ☆25Updated 3 years ago
- Morpho-MNIST: Quantitative Assessment and Diagnostics for Representation Learning (http://jmlr.org/papers/v20/19-033.html)☆89Updated 6 months ago
- Disentangled gEnerative cAusal Representation (DEAR)☆60Updated 2 years ago
- Self-Explaining Neural Networks☆13Updated 2 years ago
- Gaussian Process Prior Variational Autoencoder☆84Updated 6 years ago
- Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893☆89Updated 5 years ago
- MPVAE: Multivariate Probit Variational AutoEncoder for Multi-Label Classification☆32Updated 10 months ago
- Code accompanying paper: Meta-Learning to Improve Pre-Training☆37Updated 3 years ago
- Multimodal Mixture-of-Experts VAE☆213Updated 2 years ago
- Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 3 years ago
- Contains the code relative to the paper Partial Gromov-Wasserstein with Applications on Positive-Unlabeled Learning https://arxiv.org/abs…☆21Updated 5 years ago
- Stochastic algorithms for computing Regularized Optimal Transport☆57Updated 6 years ago