pierreablin / landing
☆18Updated last year
Related projects ⓘ
Alternatives and complementary repositories for landing
- Riemannian Optimization Using JAX☆45Updated last year
- Loopy belief propagation for factor graphs on discrete variables in JAX☆131Updated last month
- GitHub repository for the ICLR Computational Geometry & Topology Challenge 2021☆52Updated 2 years ago
- Riemannian Convex Potential Maps☆68Updated last year
- Code for Gaussian Score Matching Variational Inference☆28Updated last month
- Squared Non-monotonic Probabilistic Circuits☆19Updated 4 months ago
- An implementation of squared neural families in PyTorch☆11Updated 3 weeks ago
- A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch☆94Updated 2 months ago
- [ICML 2022] Learning Efficient and Robust Ordinary Differential \\ Equations via Invertible Neural Networks☆9Updated last year
- A library for optimization on Riemannian manifolds☆103Updated last year
- Algorithms for computations on random manifolds made easier☆86Updated 11 months ago
- Code repo for "Kernel Interpolation for Scalable Online Gaussian Processes"☆56Updated 3 years ago
- Combining smooth constraint for building DAG with normalizing flow in order to replace autoregressive transformations while keeping tract…☆44Updated last year
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆170Updated 2 years ago
- Loopy belief propagation for factor graphs on discrete variables, in JAX!☆64Updated last month
- A generic interface for linear algebra backends☆70Updated 4 months ago
- Code for efficiently sampling functions from GP(flow) posteriors☆66Updated 4 years ago
- ☆38Updated last year
- Differentiable and numerically stable implementation of the matrix exponential☆32Updated 4 years ago
- Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.☆69Updated 3 months ago
- Kernel Stein Discrepancy Descent : a method to sample from unnormalized densities☆21Updated 7 months ago
- Scalable training and inference for Probabilistic Circuits☆49Updated last week
- An implementation of EinsumNetworks in PyTorch.☆20Updated last week
- code for "Neural Conservation Laws A Divergence-Free Perspective".☆35Updated last year
- Turning SymPy expressions into JAX functions☆42Updated 3 years ago
- This repository contains the source code to perform Geometry-aware Bayesian Optimization (GaBO) on Riemannian manifolds.☆49Updated 3 years ago
- The Wasserstein Distance and Optimal Transport Map of Gaussian Processes☆49Updated 4 years ago
- Douglas-Rachford Splitting for Optimal Transport☆10Updated 3 years ago
- About A collection of AWESOME things about information geometry Topics☆148Updated 4 months ago
- Fast hyperparameter settings for non-smooth estimators:☆39Updated last year