mctorch / mctorch
A manifold optimization library for deep learning
☆236Updated 3 years ago
Related projects ⓘ
Alternatives and complementary repositories for mctorch
- Optimization with orthogonal constraints and on general manifolds☆126Updated 4 years ago
- Deep neural network kernel for Gaussian process☆198Updated 4 years ago
- Efficient PyTorch Hessian eigendecomposition tools!☆363Updated 8 months ago
- Real NVP PyTorch a Minimal Working Example | Normalizing Flow☆136Updated 4 years ago
- MMD, Hausdorff and Sinkhorn divergences scaled up to 1,000,000 samples.☆54Updated 5 years ago
- PyTorch-SSO: Scalable Second-Order methods in PyTorch☆141Updated last year
- hessian in pytorch☆185Updated 4 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Understanding normalizing flows☆131Updated 4 years ago
- A PyTorch library for two-sample tests☆237Updated last year
- Preconditioned Conjugate Gradient in Pytorch☆133Updated 8 months ago
- Pytorch implementation of Block Neural Autoregressive Flow☆175Updated 3 years ago
- Group Equivariant Convolutional Neural Networks☆97Updated 7 years ago
- Deep convolutional gaussian processes.☆78Updated 5 years ago
- ☆177Updated 5 years ago
- Repository containing Pytorch code for EKFAC and K-FAC perconditioners.☆140Updated last year
- ☆36Updated 3 years ago
- paper lists and information on mean-field theory of deep learning☆75Updated 5 years ago
- ☆258Updated last year
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆80Updated 4 years ago
- code for "Residual Flows for Invertible Generative Modeling".☆261Updated last year
- PyTorch implementation of Neural Processes☆88Updated 5 years ago
- ☆158Updated 3 months ago
- Manifold-learning flows (ℳ-flows)☆230Updated 3 years ago
- Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)☆227Updated 6 years ago
- Gabriel Peyré, Marco Cuturi, Justin Solomon, Gromov-Wasserstein Averaging of Kernel and Distance Matrices, Proc. of ICML 2016.☆73Updated 8 years ago
- Geometric loss functions between point clouds, images and volumes☆595Updated 9 months ago
- The collection of papers about combining deep learning and Bayesian nonparametrics☆118Updated 5 years ago
- Convolutional Neural Tangent Kernel☆107Updated 5 years ago
- Toolbox to integrate optimal transport loss functions using automatic differentiation and Sinkhorn's algorithm☆431Updated 6 years ago