jungtaekkim / bayeso

Related projects ⓘ

Alternatives and complementary repositories for bayeso

• jungtaekkim / bayeso-benchmarks
  Benchmark functions for Bayesian optimization
  ☆31Updated 8 months ago
• wjmaddox / drbayes
  Code Repo for "Subspace Inference for Bayesian Deep Learning"
  ☆81Updated 5 months ago
• microsoft / bayesianize
  Bayesianize: A Bayesian neural network wrapper in pytorch
  ☆87Updated 6 months ago
• automl / pybnn
  Bayesian neural network package
  ☆138Updated 3 years ago
• wjmaddox / spectralgp
  Code repo for "Function-Space Distributions over Kernels"
  ☆31Updated 3 years ago
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆109Updated 2 years ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆86Updated 4 years ago
• openopt / chop
  CHOP: An optimization library based on PyTorch, with applications to adversarial examples and structured neural network training.
  ☆76Updated 8 months ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆80Updated 4 years ago
• cambridge-mlg / convcnp
  Implementation of the Convolutional Conditional Neural Process
  ☆121Updated 3 years ago
• EmilienDupont / neural-processes
  Pytorch implementation of Neural Processes for functions and images
  ☆225Updated 2 years ago
• juho-lee / bnp
  Pytorch implementation of neural processes and variants
  ☆26Updated 4 months ago
• jinxu06 / metafun-tensorflow
  Code for "MetaFun: Meta-Learning with Iterative Functional Updates"
  ☆14Updated 4 years ago
• izmailovpavel / understandingbdl
  ☆233Updated last year
• izmailovpavel / bnn_covariate_shift
  Supporting code for the paper "Dangers of Bayesian Model Averaging under Covariate Shift"
  ☆33Updated 2 years ago
• karalets / TyXe
  Library for Bayesian Neural Networks in PyTorch (first version as published in ProbProg2020)
  ☆42Updated 3 years ago
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆147Updated 5 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆55Updated 3 years ago
• MFreidank / pysgmcmc
  Bayesian Deep Learning with Stochastic Gradient MCMC Methods
  ☆38Updated 3 years ago
• cambridge-mlg / cnn-gp
  Pytorch version of "Deep Convolutional Networks as shallow Gaussian Processes" by Adrià Garriga-Alonso, Carl Rasmussen and Laurence Aitch…
  ☆32Updated 4 years ago
• trevorcampbell / bayesian-coresets
  Automated Scalable Bayesian Inference
  ☆130Updated 2 years ago
• automl / BOAH
  BOAH: Bayesian Optimization & Analysis of Hyperparameters
  ☆67Updated 4 years ago
• google / spectral-density
  Hessian spectral density estimation in TF and Jax
  ☆115Updated 4 years ago
• Gabe-YHLee / NRAE-public
  ☆28Updated last year
• kasparmartens / NeuralProcesses
  Neural Processes implementation for 1D regression
  ☆65Updated 5 years ago
• AMLab-Amsterdam / FNP
  Implementation of the Functional Neural Process models
  ☆43Updated 4 years ago
• soobinseo / Attentive-Neural-Process
  A Pytorch Implementation of Attentive Neural Process
  ☆73Updated 5 years ago
• fKunstner / limitations-empirical-fisher
  Limitations of the Empirical Fisher Approximation
  ☆45Updated 4 years ago
• lfbo-ml / lfbo
  Code for A General Recipe for Likelihood-free Bayesian Optimization, ICML 2022
  ☆44Updated 2 years ago
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆23Updated last year