Alternatives and similar repositories for amortized-optimization-tutorial

Users that are interested in amortized-optimization-tutorial are comparing it to the libraries listed below

• facebookresearch / rcpm
  Riemannian Convex Potential Maps
  ☆67Updated 2 years ago
• massastrello / awesome-implicit-neural-models
  ☆105Updated 4 years ago
• ghliu / snopt
  Second-Order Neural ODE Optimizer, NeurIPS 2021 spotlight
  ☆55Updated 4 years ago
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆88Updated 3 years ago
• lfbo-ml / lfbo
  Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022
  ☆45Updated 3 years ago
• facebookresearch / w2ot
  Euclidean Wasserstein-2 optimal transportation
  ☆47Updated 2 years ago
• cooper-org / cooper
  A general-purpose, deep learning-first library for constrained optimization in PyTorch
  ☆146Updated 3 weeks ago
• facebookresearch / meta-ot
  Meta Optimal Transport
  ☆105Updated 2 years ago
• facebookresearch / dcem
  The Differentiable Cross-Entropy Method
  ☆124Updated 5 years ago
• CW-Huang / CP-Flow
  Convex potential flows
  ☆84Updated 4 years ago
• georgiosarvanitidis / geometric_ml
  This repository contains code for applying Riemannian geometry in machine learning.
  ☆78Updated 4 years ago
• akbir / deq-jax
  [NeurIPS'19] Deep Equilibrium Models Jax Implementation
  ☆42Updated 5 years ago
• qsh-zh / pis
  [ICLR 2022] Path integral sampler
  ☆52Updated 2 years ago
• bamos / presentations
  ☆141Updated last week
• google-deepmind / mc_gradients
  ☆172Updated last year
• CampusAI / Hamiltonian-Generative-Networks
  Re-implementation of Hamiltonian Generative Networks paper
  ☆33Updated 3 years ago
• Jiacheng-Zhu-AIML / WGPOT
  The Wasserstein Distance and Optimal Transport Map of Gaussian Processes
  ☆52Updated 5 years ago
• DiffEqML / diffeqml-research
  This repository contains code released by DiffEqML Research
  ☆91Updated 3 years ago
• google-research / ott
  ☆214Updated 3 years ago
• alisiahkoohi / Langevin-dynamics
  Sampling with gradient-based Markov Chain Monte Carlo approaches
  ☆108Updated last year
• CUAI / Neural-Manifold-Ordinary-Differential-Equations
  [NeurIPS 2020] Neural Manifold Ordinary Differential Equations (https://arxiv.org/abs/2006.10254)
  ☆122Updated 2 years ago
• google-deepmind / dm_hamiltonian_dynamics_suite
  ☆36Updated 4 years ago
• bremen79 / parameterfree
  Parameter-Free Optimizers for Pytorch
  ☆130Updated last year
• activatedgeek / svgd
  PyTorch implementation of Stein Variational Gradient Descent
  ☆47Updated 2 years ago
• xwinxu / bayeSDE
  Code for "Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations"
  ☆171Updated 3 years ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated last year
• mfinzi / residual-pathway-priors
  ☆22Updated 4 years ago
• bobby-he / Neural_Tangent_Kernel
  ☆68Updated 6 years ago
• a-norcliffe / sonode
  Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"
  ☆60Updated last year
• mctorch / mctorch
  A manifold optimization library for deep learning
  ☆249Updated 4 years ago