spdes / computational-sde-intro-lectureLinks
Lecture "A computational introduction to stochastic differential equations".
☆34Updated 6 months ago
Alternatives and similar repositories for computational-sde-intro-lecture
Users that are interested in computational-sde-intro-lecture are comparing it to the libraries listed below
Sorting:
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆108Updated last year
- Simple (and cheap!) neural network uncertainty estimation☆79Updated 3 months ago
- Code for the paper "Learning Differential Equations that are Easy to Solve"☆287Updated 4 years ago
- A Python package to learn the Koopman operator.☆65Updated 3 weeks ago
- Bayesian active learning with EPIG data acquisition☆35Updated 4 months ago
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆171Updated 3 years ago
- IVON optimizer for neural networks based on variational learning.☆80Updated last year
- Lightweight MCMC sampling for PyTorch Models aka My Corona Project☆52Updated 5 months ago
- Algorithms for computations on random manifolds made easier☆94Updated 2 years ago
- ☆18Updated 2 years ago
- PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks☆462Updated last year
- ☆206Updated 2 months ago
- Collecting research materials on neural samplers with diffusion/flow models☆59Updated 6 months ago
- ☆202Updated last year
- Regression datasets from the UCI repository with standardized test-train splits.☆52Updated 3 years ago
- Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.☆227Updated last year
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆40Updated 3 years ago
- Density Ratio Estimation via Infinitesimal Classification (AISTATS 2022 Oral)☆20Updated 3 years ago
- Bayesian Neural Network Surrogates for Bayesian Optimization☆65Updated last year
- Code repository for Particle Denoising Diffusion Sampler☆15Updated last year
- Normalizing flows in PyTorch☆440Updated last month
- Code for the paper "Beyond Deep Ensembles: A Large-Scale Evaluation of Bayesian Deep Learning under Distribution Shift"☆22Updated 2 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆74Updated 5 years ago
- Laplace approximations for Deep Learning.☆531Updated 8 months ago
- Gaussian processes in JAX and Flax.☆574Updated this week
- Official implementation of Stochastic Taylor Derivative Estimator (STDE) NeurIPS2024☆126Updated last year
- Methods and experiments for assumed density SDE approximations☆12Updated 3 years ago
- [ICML 2024] Official implementation for "Beyond ELBOs: A Large-Scale Evaluation of Variational Methods for Sampling".☆41Updated last year
- ☆12Updated 3 years ago
- PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)☆61Updated this week