MichaelArbel / Scaled-MMD-GANLinks
Scaled MMD GAN
☆36Updated 5 years ago
Alternatives and similar repositories for Scaled-MMD-GAN
Users that are interested in Scaled-MMD-GAN are comparing it to the libraries listed below
Sorting:
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated 10 months ago
- Implementation of iterative inference in deep latent variable models☆43Updated 6 years ago
- PyTorch Implementation of Neural Statistician☆60Updated 3 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- Implementation of the Sliced Wasserstein Autoencoders☆90Updated 7 years ago
- ☆91Updated 6 years ago
- ☆46Updated 7 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 6 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆46Updated 7 years ago
- ☆29Updated 4 years ago
- ☆42Updated 6 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆66Updated 5 years ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆35Updated 5 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- Experiments for the Neural Autoregressive Flows paper☆125Updated 4 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Code for "A-NICE-MC: Adversarial Training for MCMC"☆125Updated 7 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- ☆117Updated 6 years ago
- ☆37Updated 6 years ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆112Updated 6 years ago
- Code for "How to Train Deep Variational Autoencoders and Probabilistic Ladder Networks"☆101Updated 9 years ago
- Lagrangian VAE☆28Updated 7 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- Code for Stochastic Hyperparameter Optimization through Hypernetworks☆23Updated 7 years ago
- Sliced Wasserstein Generator☆23Updated 6 years ago
- Improving MMD-GAN training with repulsive loss function☆89Updated 2 years ago