WeiXiongUST / Decentralized-Proximal-Algorithm-with-Variance-ReductionLinks
This is the code used for the paper "PMGT-VR: A decentralized proximal-gradient algorithmic framework with variance reduction", prepint.
☆16Updated 3 years ago
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
Sorting:
- Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)☆33Updated 4 years ago
- Stochastic algorithms for computing Regularized Optimal Transport☆58Updated 7 years ago
- VAEs and nonlinear ICA: a unifying framework☆50Updated 6 years ago
- This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).☆52Updated 4 years ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆45Updated 2 years ago
- A tutorial on learned non-adversarial invariance in neural networks☆13Updated 6 years ago
- Code for "Learning with minibatch Wasserstein: asymptotic and gradient properties".☆13Updated 4 years ago
- Code for Sliced Gromov-Wasserstein☆69Updated 6 years ago
- Implementation of the Neural Clustering Process algorithm in Pytorch☆31Updated 5 years ago
- Learning Autoencoders with Relational Regularization☆46Updated 5 years ago
- Code for ICE-BeeM paper - NeurIPS 2020☆87Updated 4 years ago
- Deep Generative Learning via Schrödinger Bridge☆25Updated 4 years ago
- ☆59Updated 2 years ago
- Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893☆91Updated 5 years ago
- Multimodal Mixture-of-Experts VAE☆220Updated 2 years ago
- VAEs and nonlinear ICA: a unifying framework☆39Updated 5 years ago
- Learning generative models with Sinkhorn Loss☆30Updated 7 years ago
- Officially unofficial PyTorch code for the NIPS paper 'Natural-Parameter Networks: A Class of Probabilistic Neural Networks'☆11Updated 4 years ago
- A Pytorch implementation of missing data imputation using optimal transport.☆105Updated 4 years ago
- Nonlinear Independent Components Estimation (Dinh et al, 2014) in PyTorch.☆123Updated 7 years ago
- Learning the optimal transport map via input convex neural neworks☆42Updated 5 years ago
- ☆19Updated 3 years ago
- Roundtrip: density estimation with deep generative neural networks☆64Updated last year
- Repository for "Differentiable Causal Discovery from Interventional Data"☆77Updated 3 years ago
- Negative-Binomial VAE for discrete data☆18Updated 5 years ago
- Gaussian Process Prior Variational Autoencoder☆87Updated 7 years ago
- ☆63Updated 5 years ago
- PyTorch implementation for the ICLR 2020 paper "Understanding the Limitations of Variational Mutual Information Estimators"☆77Updated 5 years ago
- Code for Invariant Rep. Without Adversaries (NIPS 2018)☆35Updated 6 years ago
- Official source code repository for the ICML 2021 paper "Hierarchical VAEs Know What They Don't Know"☆31Updated 3 years ago