jungtaekkim / bayeso
Simple, but essential Bayesian optimization package
☆94Updated 3 months ago
Alternatives and similar repositories for bayeso:
Users that are interested in bayeso are comparing it to the libraries listed below
- Benchmark functions for Bayesian optimization☆33Updated last year
- Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"☆33Updated 2 years ago
- AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'☆88Updated 4 years ago
- Code Repo for "Subspace Inference for Bayesian Deep Learning"☆82Updated 10 months ago
- Bayesianize: A Bayesian neural network wrapper in pytorch☆88Updated 11 months ago
- Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)☆83Updated 4 years ago
- Bayesian neural network package☆147Updated 3 years ago
- Pytorch implementation of neural processes and variants☆28Updated 9 months ago
- Code repo for "Function-Space Distributions over Kernels"☆31Updated 4 years ago
- ☆33Updated 4 years ago
- Code for the paper "Bayesian Neural Network Priors Revisited"☆57Updated 3 years ago
- Bayesian Deep Learning with Stochastic Gradient MCMC Methods☆38Updated 3 years ago
- A community repository for benchmarking Bayesian methods☆110Updated 3 years ago
- Code for "MetaFun: Meta-Learning with Iterative Functional Updates"☆14Updated 4 years ago
- Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'☆26Updated 4 years ago
- CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.☆77Updated last year
- Implementation of the Functional Neural Process models☆43Updated 4 years ago
- Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)☆42Updated 3 years ago
- Bayesian active learning with EPIG data acquisition☆31Updated last week
- PyTorch-SSO: Scalable Second-Order methods in PyTorch☆145Updated last year
- Sample code for running deterministic variational inference to train Bayesian neural networks☆100Updated 6 years ago
- Implementation of the Convolutional Conditional Neural Process☆122Updated 3 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
- Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022☆44Updated 2 years ago
- Deep convolutional gaussian processes.☆78Updated 5 years ago
- Limitations of the Empirical Fisher Approximation☆47Updated last month
- Code for the paper Gaussian process behaviour in wide deep networks☆47Updated 6 years ago
- Deep neural network kernel for Gaussian process☆202Updated 4 years ago
- Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)☆48Updated 5 years ago
- Pre-trained Gaussian processes for Bayesian optimization☆90Updated last week