Alternatives and similar repositories for mdmm

Users that are interested in mdmm are comparing it to the libraries listed below

• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆67Updated 2 years ago
• CW-Huang / CP-Flow
  Convex potential flows
  ☆83Updated 3 years ago
• johannbrehmer / manifold-flow
  Manifold-learning flows (ℳ-flows)
  ☆230Updated 4 years ago
• PrincetonLIPS / RandomizedAutomaticDifferentiation
  Experiment code for "Randomized Automatic Differentiation"
  ☆67Updated 5 years ago
• cooper-org / cooper
  A general-purpose, deep learning-first library for constrained optimization in PyTorch
  ☆137Updated 2 months ago
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆87Updated 2 years ago
• google-research / ott
  ☆214Updated 3 years ago
• mfinzi / equivariant-MLP
  A library for programmatically generating equivariant layers through constraint solving
  ☆272Updated 2 years ago
• jacobjinkelly / easy-neural-ode
  Code for the paper "Learning Differential Equations that are Easy to Solve"
  ☆282Updated 3 years ago
• akbir / deq-jax
  [NeurIPS'19] Deep Equilibrium Models Jax Implementation
  ☆40Updated 4 years ago
• facebookincubator / flowtorch
  This library would form a permanent home for reusable components for deep probabilistic programming. The library would form and harness a…
  ☆308Updated 2 months ago
• HEmile / storchastic
  Stochastic Automatic Differentiation library for PyTorch.
  ☆206Updated 11 months ago
• massastrello / awesome-implicit-neural-models
  ☆103Updated 4 years ago
• google-deepmind / dm_hamiltonian_dynamics_suite
  ☆35Updated 3 years ago
• facebookresearch / amortized-optimization-tutorial
  Tutorial on amortized optimization for learning to optimize over continuous domains
  ☆243Updated 5 months ago
• CUAI / Neural-Manifold-Ordinary-Differential-Equations
  [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
  ☆119Updated 2 years ago
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆171Updated 3 years ago
• alisiahkoohi / Langevin-dynamics
  Sampling with gradient-based Markov Chain Monte Carlo approaches
  ☆108Updated last year
• Information-Fusion-Lab-Umass / NuX
  Normalizing Flows using JAX
  ☆84Updated last year
• nicola-decao / power_spherical
  Pytorch implementation of the Power Spherical distribution
  ☆74Updated last year
• SaitejaUtpala / rieoptax
  Riemannian Optimization Using JAX
  ☆52Updated last year
• uclnlp / torch-imle
  Implicit MLE: Backpropagating Through Discrete Exponential Family Distributions
  ☆258Updated last year
• FalkonML / falkon
  Large-scale, multi-GPU capable, kernel solver
  ☆191Updated last month
• lezcano / expm
  Differentiable and numerically stable implementation of the matrix exponential
  ☆33Updated 4 years ago
• patrick-kidger / sympytorch
  Turning SymPy expressions into PyTorch modules.
  ☆150Updated 2 years ago
• acids-ircam / pytorch_flows
  Implementation and tutorials of normalizing flows with the novel distributions module
  ☆169Updated 5 years ago
• ericjang / nf-jax
  Normalizing Flows in Jax
  ☆107Updated 5 years ago
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆77Updated 4 years ago
• cfinlay / ffjord-rnode
  Regularized Neural ODEs (RNODE)
  ☆84Updated 4 years ago
• bayesiains / nsf
  Code for Neural Spline Flows paper
  ☆278Updated 5 years ago