cooper-org / cooperLinks
A general-purpose, deep learning-first library for constrained optimization in PyTorch
☆129Updated last month
Alternatives and similar repositories for cooper
Users that are interested in cooper are comparing it to the libraries listed below
Sorting:
- Agustinus' very opiniated publication-ready plotting library☆67Updated 2 months ago
- Parameter-Free Optimizers for Pytorch☆130Updated last year
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆103Updated last year
- Sketched matrix decompositions for PyTorch☆70Updated last week
- ASDL: Automatic Second-order Differentiation Library for PyTorch☆188Updated 7 months ago
- A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch☆111Updated 4 months ago
- ☆152Updated 2 years ago
- Large-scale, multi-GPU capable, kernel solver☆190Updated last year
- {KFAC,EKFAC,Diagonal,Implicit} Fisher Matrices and finite width NTKs in PyTorch☆215Updated 3 weeks ago
- Algorithms for computations on random manifolds made easier☆91Updated last year
- Riemannian Convex Potential Maps☆67Updated 2 years ago
- IVON optimizer for neural networks based on variational learning.☆68Updated 8 months ago
- Hessian spectral density estimation in TF and Jax☆123Updated 4 years ago
- This repository contains code for applying Riemannian geometry in machine learning.☆77Updated 4 years ago
- Riemannian Optimization Using JAX☆49Updated last year
- Normalizing Flows using JAX☆83Updated last year
- Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"☆170Updated 3 years ago
- This library would form a permanent home for reusable components for deep probabilistic programming. The library would form and harness a…☆306Updated 3 weeks ago
- Code for efficiently sampling functions from GP(flow) posteriors☆72Updated 4 years ago
- Tutorial on amortized optimization for learning to optimize over continuous domains☆243Updated 4 months ago
- The Modified Differential Multiplier Method (MDMM) for PyTorch☆59Updated 4 years ago
- ☆36Updated 2 years ago
- Differentiable and numerically stable implementation of the matrix exponential☆33Updated 4 years ago
- Manifold-learning flows (ℳ-flows)☆230Updated 4 years ago
- ☆52Updated 2 years ago
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆104Updated last year
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆100Updated 2 years ago
- Stochastic Automatic Differentiation library for PyTorch.☆204Updated 10 months ago
- Convex potential flows☆83Updated 3 years ago
- Laplace Redux -- Effortless Bayesian Deep Learning☆42Updated last month