aradha / recursive_feature_machines
☆46Updated this week
Alternatives and similar repositories for recursive_feature_machines:
Users that are interested in recursive_feature_machines are comparing it to the libraries listed below
- Code for verifying deep neural feature ansatz☆17Updated last year
- Laplace Redux -- Effortless Bayesian Deep Learning☆43Updated 2 years ago
- Omnigrok: Grokking Beyond Algorithmic Data☆55Updated 2 years ago
- Bayesian inference with Python and Jax.☆32Updated 2 years ago
- Normalizing Flows with a resampled base distribution☆46Updated 2 years ago
- Euclidean Wasserstein-2 optimal transportation☆47Updated last year
- PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)☆36Updated last month
- Pytorch implementation of VAEs for heterogeneous likelihoods.☆42Updated 2 years ago
- DoG is SGD's Best Friend: A Parameter-Free Dynamic Step Size Schedule☆60Updated last year
- A general-purpose, deep learning-first library for constrained optimization in PyTorch☆115Updated last week
- Code for lin-RFM used for sparse recovery tasks☆11Updated last month
- Neat Bayesian machine learning examples☆55Updated 2 months ago
- This repository contains PyTorch implementations of various random feature maps for dot product kernels.☆21Updated 9 months ago
- Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)☆20Updated 6 years ago
- Normalizing Flows using JAX☆83Updated last year
- Composable kernels for scikit-learn implemented in JAX.☆43Updated 4 years ago
- Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling☆36Updated 3 years ago
- Treeffuser is an easy-to-use package for probabilistic prediction and probabilistic regression on tabular data with tree-based diffusion …☆42Updated last month
- ☆25Updated 2 years ago
- Kernel Stein Discrepancy Descent : a method to sample from unnormalized densities☆22Updated last year
- Transformers with doubly stochastic attention☆45Updated 2 years ago
- Code for the paper: "Independent mechanism analysis, a new concept?"☆24Updated last year
- Code for the paper "Randomly pivoted Cholesky: Practical approximation of a kernel matrix with few entry evaluations"☆28Updated 6 months ago
- Code for "Bayesian Structure Learning with Generative Flow Networks"☆87Updated 3 years ago
- Bayesian optimization with conformal coverage guarantees☆27Updated 2 years ago
- Riemannian Optimization Using JAX☆48Updated last year
- Pytorch implementation of preconditioned stochastic gradient descent (Kron and affine preconditioner, low-rank approximation precondition…☆171Updated last week
- A library for uncertainty quantification based on PyTorch☆123Updated 3 years ago
- Simple (and cheap!) neural network uncertainty estimation☆63Updated last week
- ☆53Updated 8 months ago