cmaddis / astar-sampling

Related projects: ⓘ

• Bonnevie / rebar
  A Python implementation of the gradient REBAR estimator.
  ☆45Updated 6 years ago
• y0ast / VIMCO
  Implementation of "Variational Inference for Monte Carlo Objectives"
  ☆21Updated 4 years ago
• enalisnick / paper_summaries
  Summaries and minimal implementations of ML / statistics research articles.
  ☆38Updated 3 years ago
• 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
• earcher / nvil_example
  ☆20Updated this week
• adjidieng / REM
  Reweighted Expectation Maximization
  ☆29Updated 5 years ago
• zihangdai / cegan_iclr2017
  Code release for the paper "Calibrating Energy-based Generative Adversarial Networks"
  ☆23Updated 6 years ago
• csc2541-f17 / csc2541-f17.github.io
  ☆12Updated 6 years ago
• brekelma / echo
  Echo Noise Channel for Exact Mutual Information Calculation
  ☆17Updated 4 years ago
• pemami4911 / REBAR-pytorch
  Implementation of REBAR in PyTorch
  ☆17Updated 6 years ago
• duvenaud / deep-limits
  Repo for a paper about constructing priors on very deep models.
  ☆69Updated 8 years ago
• pierrelux / rlss2017
  ☆17Updated 7 years ago
• RemiLeblond / SeaRNN-open
  Open source implementation of SeaRNN (ICLR 2018, https://openreview.net/forum?id=HkUR_y-RZ)
  ☆49Updated 6 years ago
• jiamings / ais
  Annealed Importance Sampling (AIS) for generative models.
  ☆16Updated 6 years ago
• andymiller / ReducedVarianceReparamGradients
  Reducing Reparameterization Gradient Variance code.
  ☆33Updated 7 years ago
• rhaps0dy / convnets-as-gps
  Code for "Deep Convolutional Networks as shallow Gaussian Processes"
  ☆38Updated 5 years ago
• bheinzerling / ran
  A PyTorch implementation of Recurrent Additive Networks by Lee et al. (2017)
  ☆29Updated 6 years ago
• ermongroup / BiasAndGeneralization
  ☆26Updated 5 years ago
• lxuechen / inference-suboptimality
  Code for "Inference Suboptimality in Variational Autoencoders"
  ☆14Updated 4 years ago
• t-vi / candlegp
  Gaussian Processes in Pytorch
  ☆74Updated 4 years ago
• lxuechen / bayesian_nn
  ☆17Updated this week
• wittawatj / kernel-gof
  NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.
  ☆66Updated 5 years ago
• cilvrRG / DeepLearn-Theory
  Topics on theoretical, mathematical aspects of DL
  ☆71Updated 7 years ago
• vfleaking / rnnprop
  RNNprop
  ☆36Updated 7 years ago
• wittawatj / kernel-mod
  NeurIPS 2018. Linear-time model comparison tests.
  ☆17Updated 4 years ago
• anirudh9119 / walkback_nips17
  Variational Walkback, NIPS'17
  ☆28Updated 6 years ago
• CW-Huang / torchkit
  ☆37Updated 5 years ago
• wittawatj / interpretable-test
  NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.
  ☆62Updated 6 years ago
• renmengye / meta-optim-public
  Understanding Short-Horizon Bias in Stochastic Meta-Optimization
  ☆37Updated 6 years ago