talesa / amci

Related projects: ⓘ

• franrruiz / vcd_divergence
  Code to minimize the Variational Contrastive Divergence (VCD)
  ☆27Updated 5 years ago
• gehring / fax
  ☆78Updated 3 years ago
• ssydasheng / Neural-Kernel-Network
  Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326
  ☆71Updated 6 years ago
• MethodsOfMachineLearning / probabilistic_line_search
  Probabilistic line search algorithm for stochastic optimization with a TensorFlow interface.
  ☆22Updated 7 years ago
• PrincetonLIPS / randomized_telescopes
  Code for "Efficient optimization of loops and limits with randomized telescoping sums"
  ☆27Updated 5 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 7 years ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 3 years ago
• IraKorshunova / bruno
  a deep recurrent model for exchangeable data
  ☆34Updated 4 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆51Updated 4 years ago
• CW-Huang / torchkit
  ☆37Updated 5 years ago
• thjashin / solvegp
  Sparse Orthogonal Variational Inference for Gaussian Processes (SOLVE-GP)
  ☆22Updated 3 years ago
• plai-group / tvo
  Code for the Thermodynamic Variational Objective
  ☆26Updated 2 years ago
• duvenaud / jaxde
  Prototypes of differentiable differential equation solvers in JAX.
  ☆27Updated 4 years ago
• Sohl-Dickstein / Minimum-Probability-Flow-Learning
  Matlab code implementing Minimum Probability Flow Learning.
  ☆67Updated 10 years ago
• tbrx / compiled-inference
  Train neural networks to use as SMC and importance sampling proposals
  ☆24Updated 6 years ago
• akshaykgupta / SG_MCMC
  Implementation of Stochastic Gradient MCMC algorithms
  ☆40Updated 7 years ago
• danieljtait / ladax
  Layered distributions using FLAX/JAX
  ☆10Updated 3 years ago
• gd-zhang / noisy-K-FAC
  Natural Gradient, Variational Inference
  ☆28Updated 4 years ago
• conormdurkan / lfi
  Neural likelihood-free methods in PyTorch.
  ☆38Updated 4 years ago
• Bonnevie / rebar
  A Python implementation of the gradient REBAR estimator.
  ☆45Updated 6 years ago
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆69Updated 8 years ago
• thjashin / spectral-stein-grad
  Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)
  ☆32Updated last year
• AMLab-Amsterdam / SEVDL_MGP
  Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…
  ☆31Updated 4 years ago
• jgorham / stein_discrepancy
  Code to compute the Stein discrepancy between a sample distribution and its target
  ☆16Updated 7 years ago
• lxuechen / inference-suboptimality
  Code for "Inference Suboptimality in Variational Autoencoders"
  ☆14Updated 4 years ago
• necludov / iMCMC
  ☆22Updated 4 years ago
• wittawatj / kernel-mod
  NeurIPS 2018. Linear-time model comparison tests.
  ☆17Updated 4 years ago
• cmaddis / astar-sampling
  A generic Monte Carlo method based on the Gumbel-Max trick.
  ☆32Updated 8 years ago
• franrruiz / uivi
  Code for Unbiased Implicit Variational Inference (UIVI)
  ☆13Updated 5 years ago
• cambridge-mlg / EinsumNetworks
  ☆50Updated last year