josephsalmon / OrganizationFilesLinks
☆13Updated 6 months ago
Alternatives and similar repositories for OrganizationFiles
Users that are interested in OrganizationFiles are comparing it to the libraries listed below
Sorting:
- Making your benchmark of optimization algorithms simple and open☆267Updated 3 weeks ago
- Fast hyperparameter settings for non-smooth estimators:☆40Updated 2 years ago
- This code is no longer maintained. The codebase has been moved to https://github.com/scikit-learn-contrib/skglm. This repository only ser…☆18Updated 2 years ago
- Public repo for course material on Bayesian machine learning at ENS Paris-Saclay and Univ Lille☆88Updated 6 months ago
- ☆26Updated 7 months ago
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆100Updated 2 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 6 years ago
- Proximal optimization in pure python☆118Updated 3 years ago
- Python package to fetch data from the LIBSVM website.☆20Updated 3 months ago
- El0ps: An Exact L0-Problem Solver☆12Updated 2 months ago
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆104Updated last year
- Bayesian learning and inference for state space models (SSMs) using Google Research's JAX as a backend☆61Updated last year
- A Python library for mathematical optimization☆141Updated 11 months ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Density estimation likelihood-free inference. No longer actively developed see https://github.com/mackelab/sbi instead☆73Updated 5 years ago
- Chirp instantaneous frequency estimation using stochastic differential equation Gaussian processes☆12Updated 9 months ago
- Bayes-Newton—A Gaussian process library in JAX, with a unifying view of approximate Bayesian inference as variants of Newton's method.☆235Updated last year
- Bayesian Deep Learning with Stochastic Gradient MCMC Methods☆39Updated 3 years ago
- Code for efficiently sampling functions from GP(flow) posteriors☆73Updated 4 years ago
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆78Updated last year
- Light-weighted code for Orthogonal Additive Gaussian Processes☆43Updated last year
- Various estimators of the infinite dimensional exponential family model☆15Updated 8 years ago
- Non-stationary spectral mixture kernels implemented in GPflow☆28Updated 6 years ago
- Proximal algorithms made easy in Python☆59Updated 8 years ago
- This is a collection of code samples aimed at illustrating temporal parallelization methods for sequential data.☆33Updated last year
- Generative Forests in Python☆35Updated 2 years ago
- PEPit is a package enabling computer-assisted worst-case analyses of first-order optimization methods.☆88Updated this week
- ☆40Updated 6 years ago
- Know Your Boundaries: Constraining Gaussian Processes by Variational Harmonic Features☆23Updated 6 years ago
- Differentiable and numerically stable implementation of the matrix exponential☆33Updated 4 years ago