Starred repositories
(Crafter + NetHack) in JAX. ICML 2024 Spotlight.
Koopman Kernels for Learning Dynamical Systems from Trajectory Data
A Python package to learn the Koopman operator.
Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model
tsl: a PyTorch library for processing spatiotemporal data.
Manifolds.jl provides a library of manifolds aiming for an easy-to-use and fast implementation.
A Julia package for disciplined convex programming
Taylor polynomial expansions in one and several independent variables.
A Julia package for probability distributions and associated functions.
A data structure for mathematical optimization problems
Kernel Stein Discrepancy Descent : a method to sample from unnormalized densities
Non-Linear Least Squares Minimization, with flexible Parameter settings, based on scipy.optimize, and with many additional classes and methods for curve fitting.
A JuMP extension for Stochastic Dual Dynamic Programming
A Julia interface to the Ipopt nonlinear solver
The fundamental package for scientific computing with Python.
Fast solver for L1-type problems: Lasso, sparse Logisitic regression, Group Lasso, weighted Lasso, Multitask Lasso, etc.
PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
Geometric loss functions between point clouds, images and volumes
Machine learning for multivariate data through the Riemannian geometry of positive definite matrices in Python
Parameterizing neural power spectra into periodic & aperiodic components.
