gpytorch

Here are 14 public repositories matching this topic...

BayesWatch / deep-kernel-transfer

Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)

kernel deep-learning paper regression uncertainty bayesian-methods classification kernel-methods one-shot-learning uncertainty-quantification gaussian-processes kernels meta-learning shot-learning deep-kernel-learning few-shot-learning gpytorch

Updated Jan 19, 2022
Python

SimonRennotte / Data-Efficient-Reinforcement-Learning-with-Probabilistic-Model-Predictive-Control

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Unofficial Implementation of the paper "Data-Efficient Reinforcement Learning with Probabilistic Model Predictive Control", applied to gym environments

reinforcement-learning paper pytorch uncertainty gaussian-processes model-predictive-control model-based-reinforcement-learning pytorch-implementation gpytorch control-animation

Updated Jul 27, 2021
Python

mbiparva / ax-bo-image-classification

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Hyperpatameter Bayesian Optimization for Image Classification in PyTorch

pytorch hyperparameters image-classification gpytorch botorch ax-parametrization configuration-hyperparameters adaptive-experimentation-platform

Updated Aug 20, 2019
Python

yucho147 / GP

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We have created a module to run the Gaussian process model. We have implemented the code based on GPyTorch.

pytorch gaussian-processes gpytorch

Updated Aug 20, 2020
Python

smsharma / gamma-gp

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Proof-of-principle application of Gaussian process modeling to gamma-ray analyses. Code repository associated with the paper https://arxiv.org/abs/2010.10450.

probabilistic-programming gce gaussian-processes fermi pyro gamma-ray gp neurips gpytorch ml4ps

Updated Dec 3, 2020
Jupyter Notebook

TheJacksonLab / ECG_ActiveLearning

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Dataset and code for "Coarse-Grained Density Functional Theory Predictions via Deep Kernel Learning"

pytorch nvidia gaussian-processes active-learning deep-kernel-learning gpytorch a100 dgx-a100 expected-model-output-changes electronic-coarse-graining

Updated Nov 1, 2022
Python

Devin-Taylor / gpcnn

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Uncertainty in convolutional neural network predictions using Gaussian processes

cnn pytorch uncertainty mnist variance gaussian-processes gpytorch

Updated Jun 22, 2022
Python

wearepal / ethicml-models

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Models for EthicML

pytorch bayesian-methods gaussian-processes fairness gpytorch

Updated Jun 14, 2021
Jupyter Notebook

stanbiryukov / apollo

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Highly performant and scalable out-of-the-box gaussian process regression and Bernoulli classification. Built upon GPyTorch, with a familiar sklearn api.

machine-learning scikit-learn sklearn regression pytorch gaussian-processes kriging gaussian-process gpytorch