Alternatives and similar repositories for aggregated-multitask-gp

Users that are interested in aggregated-multitask-gp are comparing it to the libraries listed below

• ae-foster / dad
  Deep Adaptive Design: Amortizing Sequential Bayesian Experimental Design
  ☆37Updated 4 years ago
• pierrejacob / unbiasedmcmc
  Unbiased Markov chain Monte Carlo with couplings
  ☆30Updated 3 years ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆90Updated 5 years ago
• rajatsen91 / CCIT
  Classifier Conditional Independence Test: A CI test that uses a binary classifier (XGBoost) for CI testing
  ☆46Updated 2 years ago
• gpschool / gpss20
  Gaussian Process and Uncertainty Quantification Summer School 2020
  ☆33Updated 2 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 6 years ago
• oxcsml / ML_bazaar
  OxCSML research group reading groups and meetings at the Department of Statistics, University of Oxford.
  ☆93Updated 3 years ago
• ialong / GPt
  Gaussian Processes for Sequential Data
  ☆18Updated 4 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆43Updated last year
• pmorenoz / ContinualGP
  Continual Gaussian Processes
  ☆31Updated 2 years ago
• csquires / causal-rep-learning-reading-group
  ☆22Updated last year
• DartML / Stein-Variational-Gradient-Descent
  code for the paper "Stein Variational Gradient Descent (SVGD): A General Purpose Bayesian Inference Algorithm"
  ☆100Updated 6 years ago
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 6 years ago
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆151Updated 6 years ago
• fbickfordsmith / epig
  Bayesian active learning with EPIG data acquisition
  ☆34Updated 2 months ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆85Updated 5 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆53Updated 5 years ago
• hughsalimbeni / bayesian_benchmarks
  A community repository for benchmarking Bayesian methods
  ☆111Updated 3 years ago
• desi-ivanova / idad
  Implicit Deep Adaptive Design (iDAD): Policy-Based Experimental Design without Likelihoods
  ☆21Updated 3 years ago
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆33Updated 3 years ago
• edfong / MP
  Martingale Posteriors with Copulas
  ☆19Updated last year
• edfong / conformal_bayes
  Conformal Bayes with importance sampling
  ☆22Updated 4 years ago
• mingzhang-yin / CoCo
  An optimization-based algorithm to accurately estimate the causal effects and robustly predict under distribution shifts. It leverages th…
  ☆14Updated last year
• idelbrid / Randomly-Projected-Additive-GPs
  Code for Randomly Projected Additive Gaussian Processes
  ☆25Updated 5 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• sremes / nssm-gp
  Non-stationary spectral mixture kernels implemented in GPflow
  ☆28Updated 6 years ago
• hughsalimbeni / DGPs_with_IWVI
  Deep Gaussian Processes with Importance-Weighted Variational Inference
  ☆39Updated 6 years ago
• akuhren / selective_gp
  Code accompanying the paper "Probabilistic Selection of Inducing Points in Sparse Gaussian Processes".
  ☆25Updated 2 years ago
• larslorch / dibs
  DiBS: Differentiable Bayesian Structure Learning, NeurIPS 2021
  ☆51Updated last year
• ImperialCollegeLondon / csml-reading-group
  Computational statistics and machine learning reading group at Imperial College London (2019-2020)
  ☆24Updated 2 weeks ago