vgsatorras / hybrid-inferenceLinks
☆21Updated 6 years ago
Alternatives and similar repositories for hybrid-inference
Users that are interested in hybrid-inference are comparing it to the libraries listed below
Sorting:
- Original PyTorch implementation of Uncertainty-guided Continual Learning with Bayesian Neural Networks, ICLR 2020☆76Updated 4 years ago
- [ICML 2020] Differentiating through the Fréchet Mean (https://arxiv.org/abs/2003.00335).☆59Updated 4 years ago
- ☆30Updated 5 years ago
- LEARNING LATENT PERMUTATIONS WITH GUMBEL-SINKHORN NETWORKS IMPLEMENTATION WITH PYTORCH☆79Updated 2 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆42Updated 2 years ago
- The Wasserstein Distance and Optimal Transport Map of Gaussian Processes☆52Updated 5 years ago
- Code for Reparameterizable Subset Sampling via Continuous Relaxations, IJCAI 2019.☆57Updated 2 years ago
- Source code for the ICML2019 paper "Subspace Robust Wasserstein Distances"☆29Updated 6 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Featurized Density Ratio Estimation☆20Updated 4 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated last year
- Implementation of the Functional Neural Process models☆42Updated 5 years ago
- ☆38Updated 5 years ago
- Structured Object-Aware Physics Prediction for Video Modeling and Planning☆32Updated 5 years ago
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆27Updated 6 years ago
- This repository contains code for applying Riemannian geometry in machine learning.☆78Updated 4 years ago
- Sliced Wasserstein Distance for Learning Gaussian Mixture Models☆66Updated 2 years ago
- Mixed-curvature Variational Autoencoders (ICLR 2020)☆65Updated 4 years ago
- Code for "Function Space Particle Optimization for Bayesian Neural Networks"☆18Updated 3 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 7 years ago
- Gaussian Process Prior Variational Autoencoder☆86Updated 6 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆90Updated 5 years ago
- A Pytorch Implementation of Attentive Neural Process☆75Updated 6 years ago
- Code for the paper Physics-as-Inverse-Graphics: Joint Unsupervised Learning of Objects and Physics from Video☆42Updated 2 years ago
- LEAP is a novel tool for discovering latent temporal causal relations.☆17Updated 4 years ago
- [AAAI20] TensorFlow implementation of the Collaborative Sampling in Generative Adversarial Networks☆24Updated 5 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- Python notebooks for Optimal Transport between Gaussian Mixture Models☆46Updated 4 years ago
- NeurIPS 2021, Code for Measuring Generalization with Optimal Transport☆28Updated 4 years ago
- This is the official source code for Sequential Neural Processes.☆40Updated 2 years ago