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 Unbiased Implicit Variational Inference (UIVI)☆14Updated 6 years ago
- ☆26Updated 6 years ago
- TensorFlow implementation of "noisy K-FAC" and "noisy EK-FAC".☆60Updated 6 years ago
- Computing various norms/measures on over-parametrized neural networks☆49Updated 6 years ago
- Geometric Certifications of Neural Nets☆41Updated 2 years ago
- Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)☆35Updated 4 years ago
- Reliable Uncertainty Estimates in Deep Neural Networks using Noise Contrastive Priors☆62Updated 5 years ago
- Implementation of the Functional Neural Process models☆43Updated 4 years ago
- Computing the eigenvalues of Neural Tangent Kernel and Conjugate Kernel (aka NNGP kernel) over the boolean cube☆47Updated 5 years ago
- ☆53Updated 10 months ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Large-batch Training, Neural Network Optimization☆9Updated 5 years ago
- [NeurIPS'19] [PyTorch] Adaptive Regularization in NN☆68Updated 5 years ago
- The Deep Weight Prior, ICLR 2019☆45Updated 4 years ago
- ☆53Updated 7 years ago
- Limitations of the Empirical Fisher Approximation☆47Updated 3 months ago
- Implementation of Information Dropout☆39Updated 7 years ago
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- Repository with code for paper "Inhibited Softmax for Uncertainty Estimation in Neural Networks"☆25Updated 6 years ago
- Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088☆54Updated 5 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated 11 months ago
- Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018☆41Updated 6 years ago
- ☆25Updated 2 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
- Code base for SRSGD.☆28Updated 5 years ago
- Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation☆69Updated 4 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
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆28Updated 6 years ago
- Pytorch optimizers implementing Hilbert Constrained Gradient Descent☆19Updated 6 years ago
- Code from the article: "The Role of Disentanglement in Generalisation" (ICLR, 2021).☆22Updated 3 years ago