konstmish / opt_methods
Benchmarking optimization methods on convex problems.
☆32Updated last year
Alternatives and similar repositories for opt_methods
Users that are interested in opt_methods are comparing it to the libraries listed below
Sorting:
- Collect optimizer related papers, data, repositories☆91Updated 6 months ago
- Adaptive gradient descent without descent☆47Updated 3 years ago
- Sampling with gradient-based Markov Chain Monte Carlo approaches☆100Updated last year
- Anderson accelerated Douglas-Rachford splitting☆29Updated 4 years ago
- ☆11Updated 4 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- This code is no longer maintained.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
- Models and code for the ICLR 2020 workshop paper "Towards Understanding Normalization in Neural ODEs"☆16Updated 5 years ago
- Computing gradients and Hessians of feed-forward networks with GPU acceleration☆18Updated last year
- Methods and experiments for assumed density SDE approximations☆12Updated 3 years ago
- Fast hyperparameter settings for non-smooth estimators:☆40Updated last year
- Tutorial materials of the Probabilistic Numerics Spring School.☆34Updated 2 years ago
- Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)☆32Updated 3 years ago
- Code for the Paper "Physics-Informed Gaussian Process Regression Generalizes Linear PDE Solvers"☆26Updated last year
- Code for the paper "Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations"☆28Updated 7 months ago
- Use scipy.optimize.minimize as a PyTorch Optimizer.☆72Updated 9 months ago
- ☆101Updated 4 years ago
- Riemannian Optimization Using JAX☆49Updated last year
- Machine Learning Function Approximation: This code implements the fully-connected Deep Neural Network (DNN) architectures considered in t…☆18Updated 4 years ago
- Optimizing neural networks via an inverse scale space flow.☆16Updated last year
- Parameter-Free Optimizers for Pytorch☆127Updated last year
- Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)☆87Updated 2 years ago
- [TMLR 2022] Curvature access through the generalized Gauss-Newton's low-rank structure: Eigenvalues, eigenvectors, directional derivative…☆17Updated last year
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- ☆21Updated 6 months ago
- Python Algorithms for Randomized Linear Algebra☆54Updated 2 years ago
- Hessian backpropagation (HBP): PyTorch extension of backpropagation for block-diagonal curvature matrix approximations☆20Updated 2 years ago
- TensorLy-Torch: Deep Tensor Learning with TensorLy and PyTorch☆77Updated 11 months ago
- Code for the book "The Elements of Differentiable Programming".☆84Updated last month
- Benchmark for bi-level optimization solvers☆44Updated 5 months ago
- ☆11Updated 3 years ago