Alternatives and similar repositories for HutchPlusPlus

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

• jaanli / hierarchical-variational-models-physics
  Hierarchical variational models for physics.
  ☆17Updated 5 years ago
• f-dangel / hbp
  Hessian backpropagation (HBP): PyTorch extension of backpropagation for block-diagonal curvature matrix approximations
  ☆20Updated 2 years ago
• eepperly / XTrace
  Code for the paper "XTrace: Making the most of every sample in stochastic trace estimation"
  ☆14Updated 2 years ago
• adamhaber / JaxEnt
  Jax-based MaxEnt
  ☆18Updated 5 years ago
• yzhwang / jax-multi-gpu-resnet50-example
  An example showing how to use jax to train resnet50 on multi-node multi-GPU
  ☆20Updated 2 years ago
• danieljtait / jax_xla_adventures
  Dive into Jax, Flax, XLA and C++
  ☆31Updated 5 years ago
• jgorham / SteinDiscrepancy.jl
  Practical tools for quantifying how well a sample approximates a target distribution
  ☆27Updated 4 years ago
• google-deepmind / annealed_flow_transport
  ☆52Updated 2 years ago
• buwantaiji / FermiFlow
  Ab-initio simulation of interacting fermions with equivariant normalizing flow.
  ☆34Updated 2 years ago
• gehring / fax
  ☆80Updated 3 years ago
• IBM / pylspack
  A lightweight, multithreaded Python package for sketching, column selection, leverage scores and related computations.
  ☆20Updated 3 weeks ago
• wangleiphy / MongeAmpereFlow
  Continuous-time gradient flow for generative modeling and variational inference
  ☆31Updated 6 years ago
• duvenaud / jaxde
  Prototypes of differentiable differential equation solvers in JAX.
  ☆27Updated 5 years ago
• j-towns / fastar
  ☆16Updated this week
• gowerrobert / StochOpt.jl
  A suite of stochastic optimization methods for solving the empirical risk minimization problem.
  ☆16Updated 5 years ago
• lezcano / expm
  Differentiable and numerically stable implementation of the matrix exponential
  ☆33Updated 4 years ago
• aki-nishimura / discontinuous-hmc
  "Discontinuous Hamiltonian Monte Carlo for sampling discrete parameters" by Akihiko Nishimura, David Dunson, Jianfeng Lu
  ☆27Updated 6 years ago
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 5 years ago
• gregversteeg / esh_dynamics
  Hamiltonian Dynamics with Non-Newtonian Momentum for Rapid Sampling
  ☆36Updated 3 years ago
• PrincetonLIPS / randomized_telescopes
  Code for "Efficient optimization of loops and limits with randomized telescoping sums"
  ☆27Updated 6 years ago
• necludov / oMCMC
  orbital MCMC
  ☆10Updated 3 years ago
• bayesianbrad / PyLFPPL
  A Low-level first-order probabilistic programming language, with in built translation constraints for automatic model checking. A flexibl…
  ☆13Updated 6 years ago
• gd-zhang / noisy-K-FAC
  Natural Gradient, Variational Inference
  ☆29Updated 5 years ago
• Runjing-Liu120 / RaoBlackwellizedSGD
  A public repository for our paper, Rao-Blackwellized Stochastic Gradients for Discrete Distributions
  ☆22Updated 6 years ago
• necludov / iMCMC
  ☆22Updated 4 years ago
• gd-zhang / Weight-Decay
  Regularization, Neural Network Training Dynamics
  ☆14Updated 5 years ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆19Updated 3 years ago
• vardigroup / TensorOrder
  A tool for weighted model counting through tensor network contraction
  ☆21Updated 3 years ago
• Sohl-Dickstein / Hamiltonian-Annealed-Importance-Sampling
  Matlab code implementing Hamiltonian Annealed Importance Sampling for importance weight, partition function, and log likelihood estimatio…
  ☆26Updated 10 years ago
• aterenin / SparseGPAX
  An ultra-lightweight JAX implementation of sparse Gaussian processes via pathwise sampling.
  ☆22Updated 4 years ago