Alternatives and similar repositories for f-EBM:

Users that are interested in f-EBM are comparing it to the libraries listed below

• thjashin / spectral-stein-grad
  Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)
  ☆33Updated last year
• wouterkool / estimating-gradients-without-replacement
  Estimating Gradients for Discrete Random Variables by Sampling without Replacement
  ☆40Updated 5 years ago
• plai-group / tvo
  Code for the Thermodynamic Variational Objective
  ☆26Updated 2 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 years ago
• baofff / BiSM
  ☆12Updated 4 years ago
• taufikxu / FD-ScoreMatching
  The official code for Efficient Learning of Generative Models via Finite-Difference Score Matching
  ☆12Updated 2 years ago
• dilinwang820 / adaptive-f-divergence
  A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"
  ☆21Updated 6 years ago
• mingzhang-yin / ARM-gradient
  Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)
  ☆28Updated 6 years ago
• wgrathwohl / LSD
  Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"
  ☆49Updated 4 years ago
• MichaelArbel / GeneralizedEBM
  ☆53Updated 9 months ago
• wgrathwohl / VERA
  ☆64Updated last year
• yilundu / improved_contrastive_divergence
  [ICML'21] Improved Contrastive Divergence Training of Energy Based Models
  ☆62Updated 3 years ago
• AMLab-Amsterdam / FNP
  Implementation of the Functional Neural Process models
  ☆43Updated 4 years ago
• ARM-gradient / ARSM
  Low-variance and unbiased gradient for backpropagation through categorical random variables, with application in variational auto-encoder…
  ☆17Updated 4 years ago
• xqding / Importance_Weighted_Autoencoders
  A PyTorch Implementation of the Importance Weighted Autoencoders
  ☆40Updated 6 years ago
• CW-Huang / NAF
  Experiments for the Neural Autoregressive Flows paper
  ☆124Updated 3 years ago
• ehoogeboom / emerging
  ☆42Updated 5 years ago
• pomonam / NoisyNaturalGradient
  TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".
  ☆60Updated 6 years ago
• cunningham-lab / igr
  ☆30Updated 4 years ago
• kefirski / bdir_vae
  simple implementation of "Improved Variational Inference with Inverse Autoregressive Flow" paper with pytorch
  ☆52Updated 7 years ago
• mingzhang-yin / SIVI
  A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…
  ☆54Updated 6 months ago
• CW-Huang / torchkit
  ☆37Updated 5 years ago
• lxuechen / inference-suboptimality
  Code for "Inference Suboptimality in Variational Autoencoders"
  ☆14Updated 5 years ago
• haoliuhl / hybrid-discriminative-generative
  Hybrid Discriminative-Generative Training via Contrastive Learning
  ☆75Updated 2 years ago
• YingzhenLi / SteinGrad
  Code release for the ICLR paper
  ☆20Updated 6 years ago
• ermongroup / higher_order_invariance
  Code for "Accelerating Natural Gradient with Higher-Order Invariance"
  ☆30Updated 5 years ago
• gd-zhang / noisy-K-FAC
  Natural Gradient, Variational Inference
  ☆29Updated 5 years ago
• GuyLor / Direct-VAE
  Implementation of the paper "Direct Optimization through argmax for discrete Variational Auto-Encoder"
  ☆14Updated 4 years ago
• SamsungLabs / semi-supervised-NFs
  Code for the paper Semi-Conditional Normalizing Flows for Semi-Supervised Learning
  ☆28Updated 3 years ago
• lxuechen / BDMC
  PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.
  ☆52Updated 3 years ago