tjoo512 / belief-matching-framework
Belief matching framework official implementation
☆39Updated 2 years ago
Alternatives and similar repositories for belief-matching-framework:
Users that are interested in belief-matching-framework are comparing it to the libraries listed below
- Last-layer Laplace approximation code examples☆83Updated 3 years ago
- ☆66Updated 5 years ago
- ☆64Updated 4 years ago
- Self-Supervised Learning with Data Augmentations Provably Isolates Content from Style☆51Updated 3 years ago
- Simple data balancing baselines for worst-group-accuracy benchmarks.☆42Updated last year
- Computing various measures and generalization bounds on convolutional and fully connected networks☆35Updated 6 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆112Updated 2 years ago
- This repository contains an official implementation of LPBNN.☆39Updated last year
- Repository for theory and methods for Out-of-Distribution (OoD) generalization☆63Updated 3 years ago
- Hybrid Discriminative-Generative Training via Contrastive Learning☆75Updated last year
- A way to achieve uniform confidence far away from the training data.☆38Updated 4 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆75Updated last year
- "Detecting Extrapolation with Local Ensembles" by David Madras, James Atwood, and Alex D'Amour☆13Updated 4 years ago
- ☆87Updated 3 years ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- The Pitfalls of Simplicity Bias in Neural Networks [NeurIPS 2020] (http://arxiv.org/abs/2006.07710v2)☆39Updated last year
- Project for the Large Scale Optimization course at Skoltech☆22Updated 6 years ago
- Code to implement the AND-mask and geometric mean to do gradient based optimization, from the paper "Learning explanations that are hard …☆39Updated 4 years ago
- ☆107Updated last year
- Official code for ICLR 2020 paper "A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning."☆100Updated 4 years ago
- ☆21Updated 2 years ago
- PyTorch implementation for the ICLR 2020 paper "Understanding the Limitations of Variational Mutual Information Estimators"☆74Updated 5 years ago
- Official Code: Estimating Model Uncertainty of Neural Networks in Sparse Information Form, ICML2020.☆30Updated 4 years ago
- Official implementation of paper Gradient Matching for Domain Generalization☆121Updated 3 years ago
- Toy datasets to evaluate algorithms for domain generalization and invariance learning.☆42Updated 3 years ago
- Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"☆49Updated 4 years ago
- Official implementation for Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder at NeurIPS 2020☆49Updated 3 years ago
- Implementation of Bayesian Gradient Descent☆37Updated last year
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆76Updated 2 years ago
- Memory efficient MAML using gradient checkpointing☆84Updated 5 years ago