Alternatives and similar repositories for invertible_densenets

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

• EmoryMLIP / OT-Flow
  PyTorch implementation of the OT-Flow approach in arXiv:2006.00104
  ☆55Updated 11 months ago
• asteroidhouse / INN-exploding-inverses
  Code for Understanding and Mitigating Exploding Inverses in Invertible Neural Networks (AISTATS 2021) http://arxiv.org/abs/2006.09347
  ☆30Updated 4 years ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated 11 months ago
• wgrathwohl / VERA
  ☆63Updated last year
• akandykeller / SelfNormalizingFlows
  ☆68Updated 2 years ago
• wgrathwohl / LSD
  Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"
  ☆49Updated 5 years ago
• locuslab / monotone_op_net
  Monotone operator equilibrium networks
  ☆53Updated 5 years ago
• CW-Huang / CP-Flow
  Convex potential flows
  ☆83Updated 3 years ago
• cunningham-lab / igr
  ☆30Updated 4 years ago
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 2 years ago
• AlexanderMath / fasth
  Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.
  ☆75Updated 11 months ago
• taufikxu / FD-ScoreMatching
  The official code for Efficient Learning of Generative Models via Finite-Difference Score Matching
  ☆12Updated 2 years ago
• point0bar1 / ebm-anatomy
  PyTorch implementation of Algorithm 1 of "On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models"
  ☆38Updated 11 months ago
• jrmcornish / cif
  PyTorch implementation of Continuously Indexed Flows paper, with many baseline normalising flows
  ☆31Updated 3 years ago
• g-benton / learning-invariances
  Codebase for Learning Invariances in Neural Networks
  ☆95Updated 2 years ago
• federicobergamin / Variational-Inference-with-Normalizing-Flows
  Personal implementation of "Variational Inference with Normalizing Flows" by [Rezende, et al., 2015] in PyTorch
  ☆22Updated 5 years ago
• TrentBrick / PyTorchDiscreteFlows
  Discrete Normalizing Flows implemented in PyTorch
  ☆114Updated 3 years ago
• sajadn / Exemplar-VAE
  Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation
  ☆69Updated 4 years ago
• AVMCMC / AuxiliaryVariationalMCMC
  Code required to reproduce the experiments in Auxiliary Variational MCMC
  ☆17Updated 6 years ago
• juntang-zhuang / TorchDiffEqPack
  ☆47Updated last year
• iamalexkorotin / Wasserstein2GenerativeNetworks
  PyTorch implementation of "Wasserstein-2 Generative Networks" (ICLR 2021)
  ☆53Updated 2 years ago
• ehoogeboom / convolution_exponential_and_sylvester
  ☆28Updated 3 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• AllanYangZhou / metalearning-symmetries
  Experiments for Meta-Learning Symmetries by Reparameterization
  ☆56Updated 4 years ago
• facebookresearch / Addressing-the-Topological-Defects-of-Disentanglement
  Repo reproducing experimental results in "Addressing the Topological Defects of Disentanglement"
  ☆22Updated 3 years ago
• YorkUCVIL / Wavelet-Flow
  Wavelet Flow: Fast Training of High Resolution Normalizing Flows
  ☆60Updated 4 years ago
• vlievin / biva-pytorch
  Official PyTorch BIVA implementation (BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling)
  ☆84Updated 2 years ago
• ermongroup / f-EBM
  Code for "Training Deep Energy-Based Models with f-Divergence Minimization" ICML 2020
  ☆36Updated 2 years ago
• ermongroup / f-dre
  Featurized Density Ratio Estimation
  ☆20Updated 4 years ago
• ehoogeboom / emerging
  ☆42Updated 6 years ago