SebFar / radial_bnn
Code to accompany the paper Radial Bayesian Neural Networks: Beyond Discrete Support In Large-Scale Bayesian Deep Learning
☆33Updated 5 years ago
Alternatives and similar repositories for radial_bnn:
Users that are interested in radial_bnn are comparing it to the libraries listed below
- Code for Unbiased Implicit Variational Inference (UIVI)☆14Updated 6 years ago
- Implementation of the Functional Neural Process models☆43Updated 4 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- ☆53Updated 9 months ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- ☆25Updated 2 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018☆41Updated 6 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated 10 months ago
- Code from the article: "The Role of Disentanglement in Generalisation" (ICLR, 2021).☆22Updated 2 years ago
- Code for the Thermodynamic Variational Objective☆26Updated 2 years ago
- Geometric Certifications of Neural Nets☆41Updated 2 years ago
- Limitations of the Empirical Fisher Approximation☆47Updated 2 months ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆34Updated 4 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆47Updated 5 years ago
- ☆26Updated 6 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- BIVA: A Very Deep Hierarchy of Latent Variables forGenerative Modeling☆29Updated 5 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated 11 months ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 3 years ago
- Contains code for the NeurIPS 2020 paper by Pan et al., "Continual Deep Learning by FunctionalRegularisation of Memorable Past"☆44Updated 4 years ago
- Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation☆69Updated 4 years ago
- ☆37Updated 5 years ago
- Implementation of Information Dropout☆39Updated 7 years ago
- Autoregressive Energy Machines☆77Updated 2 years ago
- Code for ICML 2018 paper on "Fast and Scalable Bayesian Deep Learning by Weight-Perturbation in Adam" by Khan, Nielsen, Tangkaratt, Lin, …☆113Updated 6 years ago
- Large-batch Training, Neural Network Optimization☆9Updated 5 years ago
- The Deep Weight Prior, ICLR 2019☆45Updated 4 years ago
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆92Updated 4 years ago