aleximmer / LaplaceLinks
Laplace approximations for Deep Learning.
☆505Updated last month
Alternatives and similar repositories for Laplace
Users that are interested in Laplace are comparing it to the libraries listed below
Sorting:
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆448Updated 9 months ago
- ☆241Updated 2 years ago
- BackPACK - a backpropagation package built on top of PyTorch which efficiently computes quantities other than the gradient.☆583Updated 5 months ago
- Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"☆465Updated last year
- This library would form a permanent home for reusable components for deep probabilistic programming. The library would form and harness a…☆305Updated 2 months ago
- Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper☆216Updated 7 months ago
- ☆153Updated 2 years ago
- A library for Bayesian neural network layers and uncertainty estimation in Deep Learning extending the core of PyTorch☆590Updated last month
- Gaussian processes in JAX and Flax.☆512Updated last week
- Normalizing flows in PyTorch☆384Updated last month
- Constrained optimization toolkit for PyTorch☆678Updated 3 years ago
- Code for "On Feature Collapse and Deep Kernel Learning for Single Forward Pass Uncertainty".☆111Updated 2 years ago
- ASDL: Automatic Second-order Differentiation Library for PyTorch☆186Updated 5 months ago
- Normalizing flows in PyTorch☆919Updated 5 months ago
- {KFAC,EKFAC,Diagonal,Implicit} Fisher Matrices and finite width NTKs in PyTorch☆214Updated this week
- Simple (and cheap!) neural network uncertainty estimation☆66Updated this week
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated last year
- Open-source framework for uncertainty and deep learning models in PyTorch☆393Updated last week
- ☆470Updated last month
- A library for uncertainty quantification based on PyTorch☆121Updated 3 years ago
- PyTorch implementation of normalizing flow models☆838Updated 9 months ago
- ☆572Updated 2 weeks ago
- Optimal transport tools implemented with the JAX framework, to solve large scale matching problems of any flavor.☆600Updated last week
- IVON optimizer for neural networks based on variational learning.☆66Updated 6 months ago
- Manifold-learning flows (ℳ-flows)☆229Updated 4 years ago
- Materials of the Nordic Probabilistic AI School 2022.☆180Updated 2 years ago
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆219Updated 11 months ago
- Efficient PyTorch Hessian eigendecomposition tools!☆374Updated last year
- ☆146Updated last year
- Uncertainty quantification with PyTorch☆356Updated last month