Alternatives and similar repositories for deep-kernel-learning:

Users that are interested in deep-kernel-learning are comparing it to the libraries listed below

• shib0li / DNN-MFBO
  Multi-fidelity Bayesian Optimization via Deep Neural Nets
  ☆30Updated 4 years ago
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆27Updated last year
• 000Justin000 / torchdiffeq
  Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
  ☆59Updated 4 years ago
• martinjankowiak / saasbo
  SAASBO: a package for high-dimensional bayesian optimization
  ☆43Updated 3 years ago
• treforevans / uci_datasets
  Regression datasets from the UCI repository with standardized test-train splits.
  ☆44Updated 2 years ago
• yucenli / bnn-bo
  Bayesian Neural Network Surrogates for Bayesian Optimization
  ☆49Updated 11 months ago
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆24Updated 2 years ago
• MachineLearningLifeScience / hdbo_benchmark
  Code for "A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences"
  ☆11Updated 2 months ago
• diningphil / graph-mixture-density-networks
  Official Repository of "Graph Mixture Density Networks" (ICML 2021)
  ☆26Updated 2 years ago
• cics-nd / gptorch
  Gaussian processes with PyTorch
  ☆30Updated 3 years ago
• shib0li / BMBO-DARN
  Batch Multi-Fidelity Bayesian Optimization with Deep Auto-Regressive Networks
  ☆12Updated 3 years ago
• benavoli / SkewGP
  Skew Gaussian Processes by Alessio Benavoli, Dario Azzimonti and Dario Piga
  ☆14Updated 3 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆72Updated 2 years ago
• edebrouwer / latentCCM
  Implementation of the Latent CCM paper
  ☆14Updated 10 months ago
• automl / PFNs4BO
  The official implementation of PFNs4BO: In-Context Learning for Bayesian Optimization
  ☆26Updated last year
• aleximmer / BNN-predictions
  Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021
  ☆17Updated 2 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆57Updated 3 years ago
• zi-w / Ensemble-Bayesian-Optimization
  Code repository for Ensemble Bayesian Optimization
  ☆52Updated 5 years ago
• YoungseogChung / calibrated-quantile-uq
  Training quantile models
  ☆43Updated 5 months ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆42Updated 8 months ago
• niuzehao / gnn-gp
  Official Implementation of "Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning"
  ☆13Updated 2 years ago
• a-norcliffe / sonode
  Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"
  ☆58Updated 6 months ago
• samuelstanton / conformal-bayesopt
  Bayesian optimization with conformal coverage guarantees
  ☆27Updated 2 years ago
• pmorenoz / ContinualGP
  Continual Gaussian Processes
  ☆32Updated last year
• danielkelshaw / WeightUncertainty
  PyTorch implementation of 'Weight Uncertainty in Neural Networks'
  ☆18Updated 4 years ago
• eric-vader / HD-BO-Additive-Models
  Accompanying code for AAAI 2021 publication - High-Dimensional Bayesian Optimization via Tree-Structured Additive Models
  ☆11Updated 10 months ago
• yincheng / GGP
  Code and data for the paper `Bayesian Semi-supervised Learning with Graph Gaussian Processes'
  ☆38Updated 6 years ago
• Ryan-Rhys / Heteroscedastic-BO
  Heteroscedastic Bayesian Optimisation in Numpy
  ☆21Updated 2 years ago
• spbu-math-cs / Graph-Gaussian-Processes
  Supplementary code for the AISTATS 2021 paper "Matern Gaussian Processes on Graphs".
  ☆53Updated 2 months ago
• nphdang / Bandit-BO
  Bayesian Optimization for Categorical and Continuous Inputs
  ☆21Updated 4 years ago