sarlinpe / Concrete-Dropout
A clean TensorFlow implementation of Concrete Dropout
☆23Updated 7 years ago
Alternatives and similar repositories for Concrete-Dropout:
Users that are interested in Concrete-Dropout are comparing it to the libraries listed below
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Echo Noise Channel for Exact Mutual Information Calculation☆17Updated 4 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆63Updated 4 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Code for doubly stochastic gradients☆25Updated 10 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 5 years ago
- Implementations of the ICML 2017 paper (with Yarin Gal)☆38Updated 7 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆30Updated 4 years ago
- my PhD thesis on Bayesian inference☆27Updated 11 years ago
- ☆40Updated 5 years ago
- A pytorch implementation of Amortized Stein Variational Gradient Descent/ Stein GAN☆18Updated 6 years ago
- Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning☆33Updated 4 years ago
- Scaled MMD GAN☆36Updated 5 years ago
- Code to minimize the Variational Contrastive Divergence (VCD)☆29Updated 5 years ago
- A tensorflow implementation of the NIPS 2018 paper "Variational Inference with Tail-adaptive f-Divergence"☆20Updated 6 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 3 years ago
- TensorFlow implementation of the method from Variational Dropout Sparsifies Deep Neural Networks, Molchanov et al. (2017)☆16Updated 7 years ago
- Variational Walkback, NIPS'17☆28Updated 7 years ago
- Deep Gaussian Processes with Importance-Weighted Variational Inference☆38Updated 5 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 5 years ago
- An implementation of "Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles" (http://arxiv.org/abs/1612.01474)☆34Updated 8 years ago
- ☆15Updated 8 years ago
- Exercises for the Tutorial on Approximate Bayesian Inference at the Data Science Summer School 2018☆22Updated 6 years ago
- a deep recurrent model for exchangeable data☆34Updated 4 years ago
- ☆17Updated 6 years ago
- Train neural networks to use as SMC and importance sampling proposals☆24Updated 7 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆32Updated last year
- Code for "Exponential Family Estimation via Adversarial Dynamics Embedding" (NeurIPS 2019)☆13Updated 5 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- Sparse Orthogonal Variational Inference for Gaussian Processes (SOLVE-GP)☆22Updated 3 years ago