hakeemtonalli / deep-kernel-learning

Related projects ⓘ

Alternatives and complementary repositories for deep-kernel-learning

• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆26Updated 9 months ago
• edebrouwer / latentCCM
  Implementation of the Latent CCM paper
  ☆14Updated 5 months ago
• yakovlev31 / graphpdes
  ☆14Updated 3 years ago
• shib0li / DNN-MFBO
  Multi-fidelity Bayesian Optimization via Deep Neural Nets
  ☆29Updated 3 years ago
• ratschlab / GP-VAE
  TensorFlow implementation for the GP-VAE model described in https://arxiv.org/abs/1907.04155
  ☆127Updated last year
• yucenli / bnn-bo
  Bayesian Neural Network Surrogates for Bayesian Optimization
  ☆47Updated 6 months ago
• clarafy / conformal-for-design
  ☆30Updated 2 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆71Updated 2 years ago
• spbu-math-cs / Graph-Gaussian-Processes
  Supplementary code for the AISTATS 2021 paper "Matern Gaussian Processes on Graphs".
  ☆52Updated 4 months ago
• 000Justin000 / torchdiffeq
  Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
  ☆58Updated 3 years ago
• yincheng / GGP
  Code and data for the paper `Bayesian Semi-supervised Learning with Graph Gaussian Processes'
  ☆38Updated 6 years ago
• yabozkurt / gmvae
  Repository for 'Interpretable embeddings from molecular simulations using gaussian mixture variational autoencoders'
  ☆20Updated 4 years ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆55Updated 3 years ago
• crispitagorico / torchspde
  Neural Stochastic PDEs: resolution-invariant modelling of continuous spatiotemporal dynamics
  ☆47Updated last year
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆23Updated last year
• WayneDW / Contour-Stochastic-Gradient-Langevin-Dynamics
  An elegant adaptive importance sampling algorithms for simulations of multi-modal distributions (NeurIPS'20)
  ☆39Updated 2 years ago
• Rose-STL-Lab / Spatiotemporal_UQ
  Uncertainty Quantification for Deep Spatiotemporal Forecasting
  ☆21Updated 2 months ago
• diningphil / graph-mixture-density-networks
  Official Repository of "Graph Mixture Density Networks" (ICML 2021)
  ☆26Updated 2 years ago
• yongkyung-oh / Stable-Neural-SDEs
  ☆25Updated last week
• martinjankowiak / saasbo
  SAASBO: a package for high-dimensional bayesian optimization
  ☆36Updated 3 years ago
• c-hofer / graph_filtration_learning
  ☆18Updated 3 years ago
• baoyujing / NET3
  ☆18Updated 3 years ago
• psanch21 / VACA
  ☆22Updated 2 years ago
• samuelstanton / conformal-bayesopt
  Bayesian optimization with conformal coverage guarantees
  ☆27Updated 2 years ago
• ratschlab / SVGP-VAE
  Tensorflow implementation for the SVGP-VAE model.
  ☆21Updated 3 years ago
• TinyVolt / normalizing-flows
  Implementation of normalizing flows from 1d to Nd
  ☆30Updated 3 years ago
• SeongokRyu / uq_molecule
  Uncertainty quantification of molecular property prediction using Bayesian deep learning
  ☆42Updated 5 years ago
• msesia / chr
  Conformal Histogram Regression: efficient conformity scores for non-parametric regression problems
  ☆20Updated 2 years ago
• akashmondal1810 / UncertaintyEstimation
  Uncertainty Estimation Using Deep Neural Network and Gradient Boosting Methods
  ☆23Updated 3 years ago
• yakovlev31 / graphpdes_experiments
  ☆33Updated 3 years ago