mboudiaf / Mutual-Information-Variational-BoundsLinks
A Tensorflow implementation Mutual Information estimation methods
☆47Updated 2 years ago
Alternatives and similar repositories for Mutual-Information-Variational-Bounds
Users that are interested in Mutual-Information-Variational-Bounds are comparing it to the libraries listed below
Sorting:
- PyTorch implementation for the ICLR 2020 paper "Understanding the Limitations of Variational Mutual Information Estimators"☆73Updated 5 years ago
- MINE: Mutual Information Neural Estimation in pytorch (unofficial)☆204Updated 6 years ago
- Mutual Information Neural Entropic Estimation☆27Updated last year
- ☆91Updated 3 years ago
- Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893☆88Updated 5 years ago
- Difference-of-Entropies (DoE) Estimator☆25Updated 3 years ago
- Project for the Large Scale Optimization course at Skoltech☆22Updated 6 years ago
- Stochastic algorithms for computing Regularized Optimal Transport☆57Updated 6 years ago
- Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"☆49Updated 4 years ago
- Implementation of the Sliced Wasserstein Autoencoder using PyTorch☆103Updated 6 years ago
- Official PyTorch implementation of the Fishr regularization for out-of-distribution generalization☆86Updated 3 years ago
- Code for Sliced Gromov-Wasserstein☆68Updated 5 years ago
- Learning Autoencoders with Relational Regularization☆46Updated 4 years ago
- Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation☆69Updated 4 years ago
- Tensorflow implementation of "Learning to Balance: Bayesian Meta-learning for Imbalanced and Out-of-distribution Tasks" (ICLR 2020 oral)☆101Updated 4 years ago
- Implementation of Inexact Proximal point method for Optimal Transport☆48Updated 4 years ago
- ☆63Updated 4 years ago
- Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style☆51Updated 3 years ago
- This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).☆49Updated 3 years ago
- implements optimal transport algorithms in pytorch☆97Updated 3 years ago
- Pytorch Implementation of the Nonlinear Information Bottleneck☆40Updated 10 months ago
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆28Updated 6 years ago
- [ICML 2020] Continuously Indexed Domain Adaptation☆118Updated 2 years ago
- A PyTorch Implementation of the Importance Weighted Autoencoders☆40Updated 6 years ago
- ☆40Updated 5 years ago
- ☆20Updated last year
- ☆58Updated 2 years ago
- Code for Unsupervised Learning via Meta-Learning.☆66Updated 4 years ago
- Code accompanying the ICML-2018 paper "Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace"☆38Updated 6 years ago
- ☆68Updated 6 years ago