Alternatives and similar repositories for deep-kernel-learning

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

• edebrouwer / latentCCM
  Implementation of the Latent CCM paper
  ☆16Updated last year
• TinyVolt / normalizing-flows
  Implementation of normalizing flows from 1d to Nd
  ☆36Updated 4 years ago
• Sheev13 / bnn-mean-field-vi
  ☆10Updated last year
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆24Updated 2 years ago
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆26Updated last year
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆74Updated 3 years ago
• clarafy / conformal-for-design
  ☆29Updated 2 years ago
• ratschlab / GP-VAE
  TensorFlow implementation for the GP-VAE model described in https://arxiv.org/abs/1907.04155
  ☆142Updated 2 years ago
• yucenli / bnn-bo
  Bayesian Neural Network Surrogates for Bayesian Optimization
  ☆55Updated last year
• MachineLearningLifeScience / hdbo_benchmark
  Code for "A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences"
  ☆13Updated 6 months ago
• yakovlev31 / graphpdes
  ☆14Updated 4 years ago
• gwgundersen / random-fourier-features
  Code for random Fourier features based on Rahimi and Recht's 2007 paper.
  ☆57Updated 4 years ago
• 000Justin000 / torchdiffeq
  Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
  ☆62Updated 4 years ago
• mlech26l / ode-lstms
  Code repository of the paper Learning Long-Term Dependencies in Irregularly-Sampled Time Series
  ☆118Updated 2 years ago
• tiskw / random-fourier-features
  Implementation of random Fourier features for kernel method, like support vector machine and Gaussian process model
  ☆101Updated 10 months ago
• UCLAIS / neural-ode-tutorial
  Repository for tutorial on Neural ODEs prepared for the UCL AI Society
  ☆12Updated 4 years ago
• BorealisAI / continuous-time-flow-process
  PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)
  ☆48Updated 4 years ago
• TyXe-BDL / TyXe
  ☆152Updated 2 years ago
• aleximmer / BNN-predictions
  Improving predictions of Bayesian neural nets via local linearization, AISTATS 2021
  ☆16Updated 2 years ago
• niuzehao / gnn-gp
  Official Implementation of "Graph Neural Network-Inspired Kernels for Gaussian Processes in Semi-Supervised Learning"
  ☆15Updated 2 years ago
• samuelstanton / conformal-bayesopt
  Bayesian optimization with conformal coverage guarantees
  ☆28Updated 2 years ago
• YannDubs / Neural-Process-Family
  Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
  ☆225Updated last year
• PhIMaL / temporal_normalizing_flows
  ☆11Updated 4 years ago
• wassname / attentive-neural-processes
  implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)
  ☆97Updated 5 months ago
• ludwigwinkler / pytorch_MCMC
  Lightweight MCMC sampling for PyTorch Models aka My Corona Project
  ☆49Updated 3 weeks ago
• Ryan-Rhys / Heteroscedastic-BO
  Heteroscedastic Bayesian Optimisation in Numpy
  ☆21Updated 2 years ago
• martinjankowiak / saasbo
  SAASBO: a package for high-dimensional bayesian optimization
  ☆45Updated 3 years ago
• automl / PFNs4BO
  The official implementation of PFNs4BO: In-Context Learning for Bayesian Optimization
  ☆32Updated last year
• spbu-math-cs / Graph-Gaussian-Processes
  Supplementary code for the AISTATS 2021 paper "Matern Gaussian Processes on Graphs".
  ☆53Updated 7 months ago
• ulissigroup / uncertainty_benchmarking
  Various code/notebooks to benchmark different ways we could estimate uncertainty in ML predictions.
  ☆42Updated 4 years ago