hichamjanati / srf
Random Fourier Features
☆50Updated 7 years ago
Alternatives and similar repositories for srf:
Users that are interested in srf are comparing it to the libraries listed below
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆83Updated 4 years ago
- Code for the paper Gaussian process behaviour in wide deep networks☆47Updated 6 years ago
- A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…☆54Updated 6 months ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated 10 months ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆88Updated 4 years ago
- code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"☆100Updated 6 years ago
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆57Updated 3 years ago
- The collection of recent papers about variational inference☆85Updated 5 years ago
- ☆40Updated 5 years ago
- Limitations of the Empirical Fisher Approximation☆47Updated last month
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019☆41Updated 2 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- paper lists and information on mean-field theory of deep learning☆74Updated 6 years ago
- Deep neural network kernel for Gaussian process☆202Updated 4 years ago
- Code for "A Spectral Approach to Gradient Estimation for Implicit Distributions" (ICML'18)☆33Updated last year
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- The codebase for the paper "A Tail-Index Analysis of Stochastic Gradient Noise in Deep Neural Networks"☆25Updated 5 years ago
- Implementation of the Functional Neural Process models☆43Updated 4 years ago
- Gaussian processes with PyTorch☆30Updated 3 years ago
- PyTorch implementation of Stein Variational Gradient Descent☆43Updated last year
- The collection of papers about combining deep learning and Bayesian nonparametrics☆120Updated 5 years ago
- Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…☆32Updated 5 years ago
- PyTorch implementation of Hessian Free optimisation☆43Updated 5 years ago
- Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)☆65Updated 5 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 repository for Ensemble Bayesian Optimization☆52Updated 5 years ago
- Testing Nerual Tangent Kernel (NTK) on small UCI datasets☆83Updated 5 years ago