glouppe / paper-avoLinks
Repository for the paper "Adversarial Variational Optimization of Non-Differentiable Simulators"
☆16Updated 6 years ago
Alternatives and similar repositories for paper-avo
Users that are interested in paper-avo are comparing it to the libraries listed below
Sorting:
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 5 years ago
- Forward-mode Automatic Differentiation for TensorFlow☆139Updated 7 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 6 years ago
- Implementation and demonstration of backdrop in pytorch. Code and demonstration of GP dataset generator.☆68Updated 7 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- A generic Monte Carlo method based on the Gumbel-Max trick.☆32Updated 9 years ago
- Reducing Reparameterization Gradient Variance code.☆33Updated 8 years ago
- Variational Message Passing for Structured VAE (Code for ICLR 2018 paper)☆44Updated 7 years ago
- TensorFlow, PyTorch and Numpy layers for generating Orthogonal Polynomials☆31Updated 7 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 6 years ago
- Code for NIPS 2015 "Gradient-Free Hamiltonian Monte Carlo via Effecient Kernel Exponential Families"☆25Updated 7 years ago
- Implementation of Coulomb GANs☆62Updated 3 years ago
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆64Updated 7 years ago
- Code for paper "Full-Capacity Unitary Recurrent Neural Networks"☆54Updated 8 years ago
- RL Experiments from our paper "Backpropagation Through the Void": https://arxiv.org/abs/1711.00123. Lovingly forked from OpenAI's RL Base…☆38Updated 7 years ago
- Evaluation code with models for the paper "On the Quantitative Analysis of Decoder-Based Generative Models"☆130Updated 7 years ago
- Code release for the paper "Calibrating Energy-based Generative Adversarial Networks"☆24Updated 7 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 7 years ago
- Proximal Backpropagation - a neural network training algorithm that takes implicit instead of explicit gradient steps☆42Updated 6 years ago
- Python package to sample from determinantal point processes☆18Updated 10 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆66Updated 5 years ago
- ☆26Updated 6 years ago
- Generative moment matching networks☆150Updated 9 years ago
- Deep variational inference in tensorflow☆56Updated 7 years ago
- Code for "Generative Adversarial Training for Markov Chains" (ICLR 2017 Workshop)☆80Updated 7 years ago
- Generative models and other stuff too, maybe, perhaps even probably☆16Updated 9 years ago
- A Python implementation of the gradient REBAR estimator.☆46Updated 7 years ago
- Deep GPs with GPy☆31Updated 9 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Weight initialization schemes for PyTorch nn.Modules☆70Updated 8 years ago