konstmish / opt_methodsLinks
Benchmarking optimization methods on convex problems.
☆33Updated 3 months ago
Alternatives and similar repositories for opt_methods
Users that are interested in opt_methods are comparing it to the libraries listed below
Sorting:
- Public code for running Stochastic Gradient Descent on GPs.☆39Updated 7 months ago
- PEPit is a package enabling computer-assisted worst-case analyses of first-order optimization methods.☆93Updated 2 weeks ago
- Fast hyperparameter settings for non-smooth estimators:☆40Updated 2 years ago
- Probabilistic ODE solvers are fun, but are they fast? See also: https://github.com/pnkraemer/probdiffeq for JAX code or https://github.c…☆21Updated last year
- Optimizing neural networks via an inverse scale space flow.☆16Updated last year
- Python Algorithms for Randomized Linear Algebra☆56Updated 2 years ago
- Improved LBFGS and LBFGS-B optimizers in PyTorch.☆65Updated last year
- An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.☆22Updated 4 years ago
- Source code for my PhD thesis: Backpropagation Beyond the Gradient☆20Updated 2 years ago
- Probabilistic numerical finite differences. Compute finite difference weights and differentiation matrices on scattered data sites and wi…☆11Updated 2 years ago
- Fully Bayesian Inference in GPs - Gaussian and Generic Likelihoods☆22Updated 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- This code is no longer maintained.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
- Tutorial materials of the Probabilistic Numerics Spring School.☆35Updated 2 years ago
- A Tensorflow based library for Time Series Modelling with Gaussian Processes☆32Updated last year
- Code of the Performance Estimation Toolbox (PESTO) whose aim is to ease the access to the PEP methodology for performing worst-case analy…☆55Updated last year
- A LinearOperator implementation to wrap the numerical nuts and bolts of GPyTorch☆117Updated 2 weeks ago
- Painless optimisation of constrained variables in AutoGrad, TensorFlow, PyTorch, and JAX☆23Updated 2 years ago
- ☆23Updated 2 weeks ago
- Matrix-free linear algebra in JAX.☆149Updated 2 weeks ago
- IterGP: Computation-Aware Gaussian Process Inference (NeurIPS 2022)☆42Updated 2 years ago
- "Stochasticity in Neural ODEs: An Empirical Study". Experiments from the paper☆13Updated 5 years ago
- A general-purpose, deep learning-first library for constrained optimization in PyTorch☆145Updated last week
- Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021☆24Updated 2 years ago
- Probabilistic solvers for differential equations in JAX. Adaptive ODE solvers with calibration, state-space model factorisations, and cus…☆53Updated last week
- Functional models and algorithms for sparse signal processing☆95Updated 2 years ago
- Literature and light wrappers for gaussian process models.☆47Updated 4 years ago
- Code for random Fourier features based on Rahimi and Recht's 2007 paper.☆58Updated 4 years ago
- simple JAX-/NumPy-based implementations of NGD with exact/approximate Fisher Information Matrix both in parameter-space and function-spac…☆15Updated 5 years ago
- Adaptive gradient descent without descent☆49Updated 4 years ago
- Proximal optimization in pure python☆118Updated 3 years ago