izmailovpavel / understandingbdlLinks
☆251Updated 2 years ago
Alternatives and similar repositories for understandingbdl
Users that are interested in understandingbdl are comparing it to the libraries listed below
Sorting:
- Bayesianize: A Bayesian neural network wrapper in pytorch☆90Updated last year
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆476Updated 2 years ago
- Pytorch implementation of Neural Processes for functions and images☆234Updated 3 years ago
- Contains code for the NeurIPS 2019 paper "Practical Deep Learning with Bayesian Principles"☆245Updated 6 years ago
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆93Updated 5 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆90Updated 5 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆58Updated 4 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- Testing Nerual Tangent Kernel (NTK) on small UCI datasets☆80Updated 6 years ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆86Updated 5 years ago
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆463Updated last year
- A Machine Learning workflow for Slurm.☆151Updated 5 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 6 years ago
- Code for "Uncertainty Estimation Using a Single Deep Deterministic Neural Network"☆275Updated 3 years ago
- ☆100Updated 4 years ago
- Code for "Depth Uncertainty in Neural Networks" (https://arxiv.org/abs/2006.08437)☆78Updated 2 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 3 years ago
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆227Updated last year
- Laplace approximations for Deep Learning.☆529Updated 8 months ago
- PyTorch implementation of "Weight Uncertainty in Neural Networks"☆176Updated 3 years ago
- PyTorch-SSO: Scalable Second-Order methods in PyTorch☆148Updated 2 years ago
- Code for paper "SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows"☆289Updated 4 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆101Updated 7 years ago
- Manifold-learning flows (ℳ-flows)☆231Updated 5 years ago
- Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)☆239Updated 7 years ago
- Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)☆205Updated 3 years ago
- The collection of recent papers about variational inference☆84Updated 6 years ago
- ☆68Updated 6 years ago
- Hessian spectral density estimation in TF and Jax☆124Updated 5 years ago
- A community repository for benchmarking Bayesian methods☆112Updated 4 years ago