IBM / SIC
Source code for paper Mroueh, Sercu, Rigotti, Padhi, dos Santos, "Sobolev Independence Criterion", NeurIPS 2019
☆14Updated 3 months ago
Related projects: ⓘ
- Computing various norms/measures on over-parametrized neural networks☆48Updated 5 years ago
- Geometric Certifications of Neural Nets☆41Updated last year
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆42Updated 2 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 4 years ago
- Explaining a black-box using Deep Variational Information Bottleneck Approach☆46Updated last year
- ☆26Updated 5 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆53Updated 5 years ago
- Implementation of Information Dropout☆39Updated 7 years ago
- Implicit generative models and related stuff based on the MMD, in PyTorch☆16Updated 3 years ago
- Code for paper EDDI: Efficient Dynamic Discovery of High-Value Information with Partial VAE☆37Updated last year
- "Towards Robust, Locally Linear Deep Networks" (ICLR 2019)☆10Updated 5 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 4 years ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆43Updated 3 years ago
- Implementation of the paper "Direct Optimization through argmax for discrete Variational Auto-Encoder"☆14Updated 4 years ago
- Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning☆33Updated 4 years ago
- Tools to train neural networks on structured data sets☆8Updated 4 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆62Updated 6 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 2 years ago
- Scaled MMD GAN☆36Updated 4 years ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆33Updated 4 years ago
- Code for "Neural causal learning from unknown interventions"☆98Updated 4 years ago
- Code from the article: "The Role of Disentanglement in Generalisation" (ICLR, 2021).☆22Updated 2 years ago
- Experiments for the paper "Exponential expressivity in deep neural networks through transient chaos"☆67Updated 8 years ago
- Explaining Image Classifiers by Counterfactual Generation☆27Updated 2 years ago
- Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" http…☆62Updated 4 years ago
- ☆37Updated 3 years ago
- Implementation of iterative inference in deep latent variable models☆43Updated 5 years ago
- Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018☆39Updated 5 years ago
- Code for Augment & Reduce, a scalable stochastic algorithm for large categorical distributions☆10Updated 6 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 5 years ago