Ludvins / Variational-LLALinks
Repository for Variational Linearized Laplace Approximation for Bayesian Deep Learning
☆11Updated last year
Alternatives and similar repositories for Variational-LLA
Users that are interested in Variational-LLA are comparing it to the libraries listed below
Sorting:
- The companion code for the paper "Variational inference via Wasserstein gradient flows (W-VI) M. Lambert, S. Chewi, F. Bach, S. Bonnabel…☆14Updated 2 years ago
- Code for 'Memory-based dual Gaussian processes for sequential learning' (ICML 2023)☆12Updated 2 years ago
- Code for the paper 'Continual Learning via Sequential Function-Space Variational Inference'☆25Updated 2 years ago
- Official codebase for the paper "Provable concept learning for interpretable predictions using variational inference".☆14Updated 3 years ago
- IVON optimizer for neural networks based on variational learning.☆79Updated last year
- On Uncertainty, Tempering, and Data Augmentation in Bayesian Classification☆21Updated 3 years ago
- All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)☆20Updated 3 years ago
- ☆13Updated 4 years ago
- Repository for the paper "Riemannian Laplace approximations for Bayesian neural networks"☆11Updated 2 years ago
- Posterior Network: Uncertainty Estimation without OOD Samples via Density-Based Pseudo-Counts (Neurips 2020)☆78Updated 3 years ago
- Mutual information estimators and benchmark☆55Updated 3 months ago
- Code for "Function Space Particle Optimization for Bayesian Neural Networks"☆18Updated 3 years ago
- A primer on Bayesian Neural Networks. The aim of this reading list is to facilitate the entry of new researchers into the field of Bayesi…☆57Updated 2 years ago
- Functional Regularisation for Continual Learning with Gaussian Processes☆15Updated 5 years ago
- General purpose library for BNNs, and implementation of OC-BNNs in our 2020 NeurIPS paper.☆38Updated 3 years ago
- Source code of our ICML 2025 paper "Flowing Datasets with Wasserstein over Wasserstein Gradient Flows"☆17Updated 7 months ago
- PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)☆61Updated last month
- Bayesian Neural Network Surrogates for Bayesian Optimization☆65Updated last year
- Example code of Sparse Gaussian Process Attention (ICLR 2023)☆26Updated 3 months ago
- ☆14Updated 4 years ago
- ☆33Updated 3 years ago
- Pytorch implementation of "Entropic Neural Optimal Transport via Diffusion Processes" (NeurIPS 2023, oral).☆39Updated last year
- Proceedings of ICML 2021☆10Updated 4 months ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆78Updated 2 years ago
- Official implementation of Transformer Neural Processes☆78Updated 3 years ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 4 years ago
- Principled learning method for Wasserstein distributionally robust optimization with local perturbations (ICML 2020)☆21Updated 2 years ago
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆108Updated last year
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆40Updated 3 years ago