jnhujnhu / VR-SGDLinks
A demo for VR-SGD(Comparing to some state-of-the-art algorithms).
☆13Updated 7 years ago
Alternatives and similar repositories for VR-SGD
Users that are interested in VR-SGD are comparing it to the libraries listed below
Sorting:
- Multi-task learning via Structural Regularization☆134Updated 4 years ago
- Low-rank Matrix Completion using Alternating Minimization☆23Updated 7 years ago
- This is the code for our paper: Semi-Supervised Learning With GANs: Revisiting Manifold Regularization (ICLR 2018)☆44Updated 6 years ago
- source code of the paper Graphical Generative Adversarial Networks☆71Updated 6 years ago
- Code for Implicit Regularization in Deep Matrix Factorization.☆37Updated last year
- Fast Approximate Quadratic Assignment for (Brain) Graph Matching☆16Updated 9 years ago
- Denoising Adversairal Autoencoders☆41Updated 8 years ago
- Code for "Modeling Sparse Deviations for Compressed Sensing using Generative Models", ICML 2018☆24Updated 7 years ago
- ☆46Updated 7 years ago
- Python implementation of the infomration bottleneck method (tishby et al, 1999)☆36Updated 8 years ago
- Generator loss to reduce mode-collapse and to improve the generated samples quality.☆34Updated 6 years ago
- Training Neural Networks Without Gradients: A ADMM Approach☆43Updated 7 years ago
- Code for doubly stochastic gradients☆26Updated 11 years ago
- ☆21Updated 2 years ago
- Code for the paper "Tensor Regression Networks with various Low-Rank Tensor Approximations"☆35Updated 7 years ago
- Demonising Adversarial Auto-encoder in PyTorch☆24Updated 7 years ago
- GANs with multiple Discriminators☆78Updated 2 years ago
- ☆15Updated 7 years ago
- Supporting code for "Parallel Streaming Wasserstein Barycenters"☆10Updated 8 years ago
- VEEGAN: Reducing Mode Collapse in GANs using Implicit Variational Learning☆40Updated 6 years ago
- Learning kernels to maximize the power of MMD tests☆211Updated 7 years ago
- AAAI & CVPR 2016: Preconditioned Stochastic Gradient Langevin Dynamics (pSGLD)☆35Updated 7 years ago
- Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'☆61Updated 7 years ago
- Scaled MMD GAN☆36Updated 6 years ago
- Code for Invariant Rep. Without Adversaries (NIPS 2018)☆35Updated 5 years ago
- ☆14Updated 11 years ago
- Gradient based hyperparameter optimization & meta-learning package for TensorFlow☆190Updated 5 years ago
- This is all the codes used in "Large Scale Online Kernel Learning"☆11Updated 8 years ago
- ☆39Updated 13 years ago
- Robust PCA in Python☆36Updated 12 years ago