SebFar / radial_bnnLinks
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
Sorting:
- 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
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation☆69Updated 4 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆83Updated last year
- Limitations of the Empirical Fisher Approximation☆48Updated 7 months ago
- Autoregressive Energy Machines☆78Updated 2 years ago
- ☆54Updated last year
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆54Updated 6 years ago
- Code for Unbiased Implicit Variational Inference (UIVI)☆14Updated 6 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆47Updated 6 years ago
- Cyclical Stochastic Gradient MCMC for Bayesian Deep Learning☆92Updated 4 years ago
- Implementation of "Variational Dropout and the Local Reparameterization Trick" paper with Pytorch☆48Updated 7 years ago
- Implementation of the Functional Neural Process models☆42Updated 5 years ago
- Pytorch implementation of Variational Dropout Sparsifies Deep Neural Networks☆84Updated 3 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 7 years ago
- Codebase for Learning Invariances in Neural Networks☆96Updated 3 years ago
- [NeurIPS'19] [PyTorch] Adaptive Regularization in NN☆68Updated 6 years ago
- Implementation of Information Dropout☆39Updated 8 years ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆89Updated last year
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆35Updated 5 years ago
- Multiplicative Normalizing Flow (MNF) posteriors for variational Bayesian neural networks☆66Updated 5 years ago
- Code for "Accelerating Natural Gradient with Higher-Order Invariance"☆30Updated 6 years ago
- Code for the paper Implicit Weight Uncertainty in Neural Networks☆65Updated 5 years ago
- PyTorch implementation of Bidirectional Monte Carlo, Annealed Importance Sampling, and Hamiltonian Monte Carlo.☆52Updated 4 years ago
- Hypergradient descent☆148Updated last year
- Implementation of the Sliced Wasserstein Autoencoders☆90Updated 7 years ago
- ☆32Updated 7 years ago
- Ἀνατομή is a PyTorch library to analyze representation of neural networks☆65Updated 4 months ago
- ☆27Updated 6 years ago