IBM / SIC
Source code for paper Mroueh, Sercu, Rigotti, Padhi, dos Santos, "Sobolev Independence Criterion", NeurIPS 2019
☆14Updated 7 months ago
Alternatives and similar repositories for SIC:
Users that are interested in SIC are comparing it to the libraries listed below
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆42Updated 3 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- Explaining Image Classifiers by Counterfactual Generation☆28Updated 2 years ago
- Code for paper EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE☆37Updated last year
- Code for the Thermodynamic Variational Objective☆26Updated 2 years ago
- ☆34Updated 3 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆63Updated 4 years ago
- Geometric Certifications of Neural Nets☆41Updated 2 years ago
- Implementation of the paper "Direct Optimization through argmax for discrete Variational Auto-Encoder"☆14Updated 4 years ago
- Scaled MMD GAN☆36Updated 5 years ago
- ☆26Updated 5 years ago
- Implicit generative models and related stuff based on the MMD, in PyTorch☆16Updated 4 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" http…☆62Updated 4 years ago
- ☆38Updated 3 years ago
- Code for "Accelerating Natural Gradient with Higher-Order Invariance"☆30Updated 5 years ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆34Updated 4 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆32Updated last year
- Explaining a black-box using Deep Variational Information Bottleneck Approach☆46Updated 2 years ago
- Implementation of the paper "Meta-Learning by Adjusting Priors Based on Extended PAC-Bayes Theory", Ron Amit and Ron Meir, ICML 2018☆22Updated 5 years ago
- Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018☆41Updated 6 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆63Updated 6 years ago
- Implementation of Information Dropout☆39Updated 7 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation☆69Updated 4 years ago
- An Empirical Study of Invariant Risk Minimization☆27Updated 4 years ago
- NeurIPS 2018. Linear-time model comparison tests.☆18Updated 5 years ago
- Code for Fong and Vedaldi 2017, "Interpretable Explanations of Black Boxes by Meaningful Perturbation"☆30Updated 5 years ago
- Monotone operator equilibrium networks☆51Updated 4 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago