yaringal / acquisition_exampleLinks
Train a simple convnet on the MNIST dataset and evaluate the BALD acquisition function
☆16Updated 7 years ago
Alternatives and similar repositories for acquisition_example
Users that are interested in acquisition_example 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
- NeurIPS 2016. Linear-time interpretable nonparametric two-sample test.☆64Updated 7 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- An implementation of "Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles" (http://arxiv.org/abs/1612.01474)☆34Updated 8 years ago
- Repository of code for the experiments for the ICLR submission "An Empirical Investigation of Catastrophic Forgetting in Gradient-Based N…☆68Updated 11 years ago
- Gaussian Processes in Pytorch☆75Updated 5 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆65Updated 5 years ago
- Summaries and minimal implementations of ML / statistics research articles.☆39Updated 4 years ago
- ☆62Updated 8 years ago
- Deep Generative Models with Stick-Breaking Priors☆95Updated 9 years ago
- Implementation of Stochastic Gradient MCMC algorithms☆41Updated 8 years ago
- A generic Monte Carlo method based on the Gumbel-Max trick.☆32Updated 9 years ago
- Variational Dropout Sparsifies Deep Neural Networks (Molchanov et al. 2017) by Chainer☆18Updated 8 years ago
- Implementation of Conditionally Shifted Neurons by Munkhdalai et al. (https://arxiv.org/pdf/1712.09926.pdf)☆28Updated 7 years ago
- Probabilistic classification in PyTorch/TensorFlow/scikit-learn with Fenchel-Young losses☆186Updated last year
- Implementations of the ICML 2017 paper (with Yarin Gal)☆38Updated 7 years ago
- ☆134Updated 5 years ago
- Layerwise Relevance Propagation with Deep Taylor Series in TensorFlow☆72Updated 8 years ago
- NeurIPS 2017 best paper. An interpretable linear-time kernel goodness-of-fit test.☆67Updated 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 "Deep Convolutional Networks as shallow Gaussian Processes"☆39Updated 6 years ago
- Variational Fourier Features☆86Updated 4 years ago
- Demos demonstrating the difference between homoscedastic and heteroscedastic regression with dropout uncertainty.☆140Updated 9 years ago
- Code for "Systematic Generalization: What Is Required and Can It Be Learned"☆37Updated 6 years ago
- Generative Adversarial Networks in Keras☆46Updated 4 years ago
- Github page for the preprint paper "InfoCatVAE: Representation Learning with Categorical Variational Autoencoders"☆14Updated 4 years ago
- Interpreting neural networks via the STREAK algorithm (streaming weak submodular maximization)☆23Updated 7 years ago
- Small Python library to automatically set CUDA_VISIBLE_DEVICES to the least loaded device on multi-GPU systems.☆107Updated 2 years ago
- ☆63Updated 9 years ago