WeiXiongUST / Decentralized-Proximal-Algorithm-with-Variance-Reduction
This is the code used for the paper "PMGT-VR: A decentralized proximal-gradient algorithmic framework with variance reduction", prepint.
☆15Updated 2 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
- Stochastic algorithms for computing Regularized Optimal Transport☆57Updated 6 years ago
- Deep Generative Learning via Schrödinger Bridge☆20Updated 3 years ago
- Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)☆32Updated 3 years ago
- Code for "Learning with minibatch Wasserstein: asymptotic and gradient properties".☆13Updated 3 years ago
- Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport☆43Updated last year
- A tutorial on learned non-adversarial invariance in neural networks☆13Updated 5 years ago
- Officially unofficial PyTorch code for the NIPS paper 'Natural-Parameter Networks: A Class of Probabilistic Neural Networks'☆11Updated 3 years ago
- This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).☆48Updated 3 years ago
- VAEs and nonlinear ICA: a unifying framework☆46Updated 5 years ago
- Code for Sliced Gromov-Wasserstein☆66Updated 5 years ago
- Learning the optimal transport map via input convex neural neworks☆40Updated 4 years ago
- Learning Autoencoders with Relational Regularization☆45Updated 4 years ago
- PyTorch implementation for the ICLR 2020 paper "Understanding the Limitations of Variational Mutual Information Estimators"☆74Updated 4 years ago
- Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893☆85Updated 4 years ago
- A new mini-batch framework for optimal transport in deep generative models, deep domain adaptation, approximate Bayesian computation, col…☆37Updated last year
- Implementation of "Learning latent subspaces in variational autoencoders"☆20Updated 5 years ago
- Efficient Conditionally Invariant Representation Learning (ICLR 2023, Oral)☆21Updated 2 years ago
- ☆13Updated 4 years ago
- VCCA Pytorch Implementation on MNIST dataset☆16Updated 6 years ago
- ☆57Updated last year
- Deep Large-Scale Inference UsingKnockoffs☆11Updated 3 years ago
- Learning generative models with Sinkhorn Loss☆28Updated 6 years ago
- Proximal Optimal Transport Modeling of Population Dynamics (AISTATS 2022)☆16Updated last year
- A set of tests for evaluating large-scale algorithms for Wasserstein-2 transport maps computation (NeurIPS 2021)☆38Updated 2 years ago
- ☆23Updated 3 years ago
- ☆20Updated 4 years ago
- Code accompanying paper: Meta-Learning to Improve Pre-Training☆37Updated 3 years ago
- Rethinking Bias-Variance Trade-off for Generalization of Neural Networks☆49Updated 3 years ago
- This is the official repo for the experiments in the paper "Bilevel Programming for Hyperparameter Optimization and Meta-Learning"☆30Updated 6 years ago
- Neural Tangent Kernel Papers☆104Updated 2 weeks ago