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
- Echo Noise Channel for Exact Mutual Information Calculation☆17Updated 4 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Code for doubly stochastic gradients☆25Updated 10 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 4 years ago
- Code for "Differentiable Compositional Kernel Learning for Gaussian Processes" https://arxiv.org/abs/1806.04326☆71Updated 6 years ago
- Code for "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 5 years ago
- Code accompanying the paper "Learning Permutations with Sinkhorn Policy Gradient"☆39Updated 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
- Implementations of the ICML 2017 paper (with Yarin Gal)☆39Updated 7 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆63Updated 4 years ago
- Example implementation of the Bayesian neural network in "Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteri…☆31Updated 4 years ago
- An implementation of "Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles" (http://arxiv.org/abs/1612.01474)☆34Updated 8 years ago
- TensorFlow implementation of the method from Variational Dropout Sparsifies Deep Neural Networks, Molchanov et al. (2017)☆16Updated 7 years ago
- ☆47Updated 5 months ago
- ☆26Updated 5 years ago
- Code for Stochastic Hyperparameter Optimization through Hypernetworks☆23Updated 6 years ago
- ☆17Updated 6 years ago
- Notebooks for IPAM Tutorial, March 15 2019☆24Updated 5 years ago
- Replication of the paper "Variational Dropout and the Local Reparameterization Trick" using Lasagne.☆33Updated 7 years ago
- Code for "Exponential Family Estimation via Adversarial Dynamics Embedding" (NeurIPS 2019)☆13Updated 5 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆32Updated last year
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 5 years ago
- A pytorch implementation of Amortized Stein Variational Gradient Descent/ Stein GAN☆18Updated 6 years ago
- Geometric Certifications of Neural Nets☆41Updated 2 years ago
- Understanding Short-Horizon Bias in Stochastic Meta-Optimization☆37Updated 6 years ago
- ☆13Updated 6 years ago
- ZForcing Repo☆40Updated 7 years ago
- a deep recurrent model for exchangeable data☆34Updated 4 years ago
- Stochastic Gradient Riemannian Langevin Dynamics☆33Updated 9 years ago