bneyshabur / path-sgd
Path-SGD: Path-Normalized Optimization in Deep Neural Networks
☆19Updated 6 years ago
Alternatives and similar repositories for path-sgd:
Users that are interested in path-sgd are comparing it to the libraries listed below
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- Repository for theory and methods for Out-of-Distribution (OoD) generalization☆63Updated 3 years ago
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆42Updated last year
- ☆64Updated 4 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆57Updated 3 years ago
- ☆34Updated 4 years ago
- The codebase for the paper "A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks"☆25Updated 5 years ago
- This repository contains implementations of the paper, Bayesian Model-Agnostic Meta-Learning.☆60Updated 5 years ago
- ☆40Updated 5 years ago
- Rethinking Bias-Variance Trade-off for Generalization of Neural Networks☆49Updated 4 years ago
- ☆31Updated 2 years ago
- Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"☆49Updated 4 years ago
- ☆89Updated 3 years ago
- ☆40Updated 5 years ago
- Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893☆86Updated 5 years ago
- This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).☆49Updated 3 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆88Updated 4 years ago
- Implementation of Bayesian Gradient Descent☆37Updated last year
- Implementation of 'DIVA: Domain Invariant Variational Autoencoders'☆101Updated 5 years ago
- Computing various measures and generalization bounds on convolutional and fully connected networks☆35Updated 6 years ago
- Pytorch Implementation of the Nonlinear Information Bottleneck☆39Updated 9 months ago
- Coresets via Bilevel Optimization☆65Updated 4 years ago
- ☆58Updated 2 years ago
- Original PyTorch implementation of Uncertainty-guided Continual Learning with Bayesian Neural Networks, ICLR 2020☆74Updated 3 years ago
- Regularized Learning under label shifts☆18Updated 5 years ago
- ☆30Updated 3 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Certifying Some Distributional Robustness with Principled Adversarial Training (https://arxiv.org/abs/1710.10571)☆45Updated 6 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)☆32Updated 3 years ago