carnotresearch / cr-sparseLinks
Functional models and algorithms for sparse signal processing
☆95Updated 2 years ago
Alternatives and similar repositories for cr-sparse
Users that are interested in cr-sparse are comparing it to the libraries listed below
Sorting:
- Differentiable and gpu enabled fast wavelet transforms in JAX.☆47Updated last year
- A JAX-based research framework for writing differentiable numerical simulators with arbitrary discretizations☆132Updated last year
- ☆10Updated 3 years ago
- PyProximal – Proximal Operators and Algorithms in Python☆77Updated last month
- Stencil computations in JAX☆71Updated 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- This code is no longer maintained.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
- Turning SymPy expressions into JAX functions☆45Updated 4 years ago
- A simple and general framework for signal decomposition☆72Updated 10 months ago
- Proximal optimization in pure python☆118Updated 3 years ago
- Code for 'Periodic Activation Functions Induce Stationarity' (NeurIPS 2021)☆19Updated 4 years ago
- Quasi-Newton algorithm for joint-diagonalization☆33Updated 3 years ago
- A JAX-based research framework for differentiable and parallelizable acoustic simulations, on CPU, GPUs and TPUs☆184Updated last year
- Pytorch implementation of SuperPolyak subgradient method.☆43Updated 3 years ago
- Minimal Implementation of Bayesian Optimization in JAX☆100Updated 6 months ago
- Visualize, create, and operate on pytrees in the most intuitive way possible.☆45Updated 10 months ago
- Differentiable interface to FEniCS/Firedrake for JAX using dolfin-adjoint/pyadjoint☆104Updated 2 years ago
- an Open Collaborative project to explore the implications — theoretical or practical — of the PDE perspective of ConvNets☆22Updated 2 years ago
- Gradient-informed particle MCMC methods☆12Updated last year
- Modular Optimisation tools for solving inverse problems☆27Updated 4 months ago
- Numerical integration in arbitrary dimensions on the GPU using PyTorch / TF / JAX☆209Updated 3 months ago
- Lightweight library of stochastic gradient MCMC algorithms written in JAX.☆105Updated 2 years ago
- Approximate inference for Markov Gaussian processes using iterated Kalman smoothing, in JAX☆102Updated 2 years ago
- Wraps PyTorch code in a JIT-compatible way for JAX. Supports automatically defining gradients for reverse-mode AutoDiff.☆58Updated 3 months ago
- Riemannian Optimization Using JAX☆53Updated 2 years ago
- L1-regularized least squares with PyTorch☆71Updated 2 years ago
- Exponential families for JAX☆75Updated 2 weeks ago
- Normalizing Flows using JAX☆85Updated last year
- Improved LBFGS and LBFGS-B optimizers in PyTorch.☆65Updated last year
- JAX bindings to the Flatiron Institute Non-uniform Fast Fourier Transform (FINUFFT) library☆106Updated last week
- Hamiltonain Monte Carlo in Python☆40Updated 6 years ago