roosephu / deep_matrix_factorizationLinks
Code for Implicit Regularization in Deep Matrix Factorization.
☆37Updated last year
Alternatives and similar repositories for deep_matrix_factorization
Users that are interested in deep_matrix_factorization are comparing it to the libraries listed below
Sorting:
- Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"☆29Updated 6 years ago
- Stochastic algorithms for computing Regularized Optimal Transport☆58Updated 7 years ago
- Code for Sliced Gromov-Wasserstein☆69Updated 5 years ago
- ☆41Updated 5 years ago
- Implementation of the Sliced Wasserstein Autoencoder using PyTorch☆103Updated 6 years ago
- Implementation of LDMnet in pytorch☆22Updated 6 years ago
- Variational auto encoder in pytorch☆57Updated 6 years ago
- The code for Differentiable Linearized ADMM (ICML 2019)☆36Updated 5 years ago
- A Tensorflow implementation Mutual Information estimation methods☆47Updated 2 years ago
- Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)☆105Updated 5 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Updated 5 years ago
- Sliced Wasserstein Distance for Learning Gaussian Mixture Models☆66Updated 2 years ago
- Code for paper: SDE-Net: Equipping Deep Neural network with Uncertainty Estimates☆114Updated 4 years ago
- [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).☆56Updated 3 years ago
- Nonlinear SVGD for Learning Diversified Mixture Models☆13Updated 6 years ago
- Learning Autoencoders with Relational Regularization☆46Updated 4 years ago
- VCCA Pytorch Implementation on MNIST dataset☆16Updated 7 years ago
- Experiments with Neural ODEs and Adversarial Attacks☆45Updated 6 years ago
- ☆12Updated 6 years ago
- ☆47Updated last year
- Anonymized code for ICLR 2019 submission "Understanding and Improving Interpolation in Autoencoders via an Adversarial Regularizer"☆20Updated 6 years ago
- Implementation of 'DIVA: Domain Invariant Variational Autoencoders'☆104Updated 5 years ago
- Learning generative models with Sinkhorn Loss☆30Updated 6 years ago
- code for paper "Graph Structure of Neural Networks"☆155Updated 3 years ago
- A Python implementation of Monge optimal transportation☆49Updated last year
- LEARNING LATENT PERMUTATIONS WITH GUMBEL-SINKHORN NETWORKS IMPLEMENTATION WITH PYTORCH☆79Updated 2 years ago
- Code for experimentation on graph scattering transforms☆30Updated 5 years ago
- This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).☆50Updated 4 years ago
- code for the paper in NeurIPS 2019☆40Updated 2 years ago
- Sliced Wasserstein Generator☆23Updated 6 years ago