Alternatives and similar repositories for Decentralized-Proximal-Algorithm-with-Variance-Reduction

Users that are interested in Decentralized-Proximal-Algorithm-with-Variance-Reduction are comparing it to the libraries listed below

• dcmoyer / invariance-tutorial
  A tutorial on learned non-adversarial invariance in neural networks
  ☆13Updated 6 years ago
• kilianFatras / minibatch_Wasserstein
  Code for "Learning with minibatch Wasserstein: asymptotic and gradient properties".
  ☆13Updated 4 years ago
• vivienseguy / Large-Scale-OT
  Stochastic algorithms for computing Regularized Optimal Transport
  ☆58Updated 7 years ago
• HongtengXu / Relational-AutoEncoders
  Learning Autoencoders with Relational Regularization
  ☆46Updated 5 years ago
• YangLabHKUST / DGLSB
  Deep Generative Learning via Schrödinger Bridge
  ☆25Updated 4 years ago
• thibsej / unbalanced_gromov_wasserstein
  Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport
  ☆45Updated 2 years ago
• tvayer / SGW
  Code for Sliced Gromov-Wasserstein
  ☆69Updated 6 years ago
• siamakz / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆50Updated 6 years ago
• danielgreenfeld3 / XIC
  Robust Learning with the Hilbert-Schmidt Independence Criterion
  ☆49Updated 5 years ago
• reiinakano / invariant-risk-minimization
  Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893
  ☆91Updated 5 years ago
• js05212 / PyTorch-for-NPN
  Officially unofficial PyTorch code for the NIPS paper 'Natural-Parameter Networks: A Class of Probabilistic Neural Networks'
  ☆11Updated 4 years ago
• vislearn / GIN
  Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)
  ☆33Updated 4 years ago
• fpcasale / GPPVAE
  Gaussian Process Prior Variational Autoencoder
  ☆87Updated 7 years ago
• fengliu90 / DK-for-TST
  This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
  ☆53Updated 4 years ago
• abidlabs / contrastive_vae
  Contrastive Variational Autoencoders
  ☆72Updated 6 years ago
• xwshen51 / DEAR
  Disentangled gEnerative cAusal Representation (DEAR)
  ☆65Updated 3 years ago
• iffsid / mmvae
  Multimodal Mixture-of-Experts VAE
  ☆221Updated 2 years ago
• anniesch / jtt
  Code for "Just Train Twice: Improving Group Robustness without Training Group Information"
  ☆73Updated last year
• JakobHavtorn / hvae-oodd
  Official source code repository for the ICML 2021 paper "Hierarchical VAEs Know What They Don't Know"
  ☆31Updated 4 years ago
• khainb / Mini-batch-OT
  A new mini-batch framework for optimal transport in deep generative models, deep domain adaptation, approximate Bayesian computation, col…
  ☆36Updated 2 years ago
• AmanDaVinci / SENN
  Self-Explaining Neural Networks
  ☆44Updated 6 years ago
• franciscovargas / GP_Sinkhorn
  GP Sinkhorn Implementation, paper: https://www.mdpi.com/1099-4300/23/9/1134
  ☆23Updated 3 years ago
• younglululu / DeepPINK
  DeepPINK: reproducible feature selection in deep neural networks
  ☆22Updated last year
• ermongroup / smile-mi-estimator
  PyTorch implementation for the ICLR 2020 paper "Understanding the Limitations of Variational Mutual Information Estimators"
  ☆77Updated 5 years ago
• uhlerlab / discrepancy_vae
  code for paper: Identifiability Guarantees for Causal Disentanglement from Soft Interventions
  ☆15Updated 2 years ago
• is0383kk / Dirichlet-VAE
  Dirichlet-Variational Auto-Encoder by PyTorch
  ☆24Updated 4 months ago
• paultsw / nice_pytorch
  Nonlinear Independent Components Estimation (Dinh et al, 2014) in PyTorch.
  ☆123Updated 7 years ago
• ilkhem / icebeem
  Code for ICE-BeeM paper - NeurIPS 2020
  ☆87Updated 4 years ago
• siplab-gt / generative-causal-explanations
  Code for "Generative causal explanations of black-box classifiers"
  ☆35Updated 5 years ago
• linyongver / ZIN_official
  This is the implementation for the NeurIPS 2022 paper: ZIN: When and How to Learn Invariance Without Environment Partition?
  ☆22Updated 3 years ago