Alternatives and similar repositories for Replica_Exchange_Stochastic_Gradient_MCMC

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

• pfnet-research / einconv
  ☆47Updated 6 years ago
• AlexanderMath / fasth
  Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.
  ☆76Updated last year
• fmeirinhos / pytorch-hessianfree
  PyTorch implementation of Hessian Free optimisation
  ☆43Updated 5 years ago
• ymalitsky / adaptive_GD
  Adaptive gradient descent without descent
  ☆48Updated 3 years ago
• noahgolmant / SGLD
  Stochastic Gradient Langevin Dynamics for Bayesian learning
  ☆35Updated 3 years ago
• ruqizhang / csgmcmc
  Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning
  ☆92Updated 4 years ago
• cambridge-mlg / cnn-gp
  Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…
  ☆32Updated 5 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆53Updated 5 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• bobby-he / Neural_Tangent_Kernel
  ☆67Updated 6 years ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated last year
• fKunstner / limitations-empirical-fisher
  Limitations of the Empirical Fisher Approximation
  ☆48Updated 7 months ago
• patrick-kidger / FasterNeuralDiffEq
  Code for "'Hey, that's not an ODE:' Faster ODE Adjoints via Seminorms" (ICML 2021)
  ☆88Updated 2 years ago
• cunningham-lab / igr
  ☆30Updated 4 years ago
• WayneDW / Contour-Stochastic-Gradient-Langevin-Dynamics
  An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)
  ☆42Updated 3 years ago
• lezcano / expRNN
  Optimization with orthogonal constraints and on general manifolds
  ☆130Updated 5 years ago
• EmoryMLIP / OT-Flow
  PyTorch implementation of the OT-Flow approach in arXiv:2006.00104
  ☆55Updated last year
• rajatvd / NeuralODE
  Experiments with Neural ODEs and Adversarial Attacks
  ☆45Updated 6 years ago
• cemanil / LNets
  Lipschitz Neural Networks described in "Sorting Out Lipschitz Function Approximation" (ICML 2019).
  ☆57Updated 5 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆32Updated 4 years ago
• f-dangel / hbp
  Hessian backpropagation (HBP): PyTorch extension of backpropagation for block-diagonal curvature matrix approximations
  ☆21Updated 2 years ago
• abdulfatir / planar-flow-pytorch
  Pytorch implementation of Planar Flow
  ☆17Updated 5 years ago
• juntang-zhuang / TorchDiffEqPack
  ☆48Updated last year
• TrentBrick / PyTorchDiscreteFlows
  Discrete Normalizing Flows implemented in PyTorch
  ☆113Updated 4 years ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆83Updated last year
• ghliu / mean-field-fcdnn
  ☆28Updated 6 years ago
• henripal / sgld
  ☆59Updated 6 years ago
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆39Updated 5 years ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 4 years ago