GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration

28 September 2018

Papers citing "GPyTorch: Blackbox Matrix-Matrix Gaussian Process Inference with GPU Acceleration"

50 / 207 papers shown

Title
Time-Varying Transition Matrices with Multi-task Gaussian Processes Ekin Ugurel 16 0 0 20 Jun 2023
Probabilistic Unrolling: Scalable, Inverse-Free Maximum Likelihood Estimation for Latent Gaussian Models Alexander Lin Bahareh Tolooshams Yves Atchadé Demba E. Ba 36 1 0 05 Jun 2023
Computationally Efficient Data-Driven MPC for Agile Quadrotor Flight Wonoo Choo E. Kayacan 30 0 0 26 May 2023
Vecchia Gaussian Process Ensembles on Internal Representations of Deep Neural Networks Felix Jimenez Matthias Katzfuss BDL UQCV 66 1 0 26 May 2023
Inverse Protein Folding Using Deep Bayesian Optimization Natalie Maus Yimeng Zeng Daniel A. Anderson Phillip M. Maffettone Aaron C. Solomon Peyton Greenside Osbert Bastani Jacob R. Gardner 37 2 0 25 May 2023
Kernel Interpolation with Sparse Grids Mohit Yadav Daniel Sheldon Cameron Musco 23 5 0 23 May 2023
Uniform approximation of common Gaussian process kernels using equispaced Fourier grids A. Barnett P. Greengard M. Rachh 28 7 0 18 May 2023
A Global-Local Approximation Framework for Large-Scale Gaussian Process Modeling Akhil Vakayil Roshan Joseph 30 2 0 17 May 2023
Expressive Mortality Models through Gaussian Process Kernels M. Ludkovski Jimmy Risk 26 1 0 02 May 2023
Learning battery model parameter dynamics from data with recursive Gaussian process regression A. Aitio Dominik Jöst D. Sauer David A. Howey 19 5 0 26 Apr 2023
Ensemble Gaussian Processes for Adaptive Autonomous Driving on Multi-friction Surfaces Tomávs Nagy Ahmad Amine Truong X. Nghiem Ugo Rosolia Zirui Zang Rahul Mangharam 37 7 0 23 Mar 2023
A High-Performance Accelerator for Super-Resolution Processing on Embedded GPU W. Zhao Qi Sun Yang Bai Wenbo Li Haisheng Zheng Bei Yu Martin D. F. Wong SupR 47 8 0 16 Mar 2023
Gaussian Max-Value Entropy Search for Multi-Agent Bayesian Optimization Haitong Ma Tianpeng Zhang Yixuan Wu Flavio du Pin Calmon Na Li 37 10 0 10 Mar 2023
Unleashing the Potential of Acquisition Functions in High-Dimensional Bayesian Optimization Jiayu Zhao Renyu Yang Shenghao Qiu Zheng Wang 29 4 0 16 Feb 2023
Returning The Favour: When Regression Benefits From Probabilistic Causal Knowledge S. Bouabid Jake Fawkes Dino Sejdinovic CML 49 0 0 26 Jan 2023
On the role of Model Uncertainties in Bayesian Optimization Jonathan Foldager Mikkel Jordahn Lars Kai Hansen Michael Riis Andersen 32 5 0 14 Jan 2023
QoS-Aware Resource Management for Multi-phase Serverless Workflows with Aquatope Zhuangzhuang Zhou Yanqi Zhang Christina Delimitrou 34 1 0 28 Dec 2022
Reconstructing Kernel-based Machine Learning Force Fields with Super-linear Convergence Stefan Blücher Klaus-Robert Muller Stefan Chmiela 31 4 0 24 Dec 2022
Multi-Instance Partial-Label Learning: Towards Exploiting Dual Inexact Supervision Wei Tang Weijia Zhang Min-Ling Zhang 19 12 0 18 Dec 2022
Mining Explainable Predictive Features for Water Quality Management C. Muldoon Levent Gorgu J. O'Sullivan W. Meijer Gregory M. P. O'Hare FAtt 21 0 0 08 Dec 2022
Deep Kernel Learning for Mortality Prediction in the Face of Temporal Shift Miguel Rios A. Abu-Hanna OOD 30 1 0 01 Dec 2022
Gaussian Process Barrier States for Safe Trajectory Optimization and Control Hassan Almubarak Manan S. Gandhi Yuichiro Aoyama N. Sadegh Evangelos A. Theodorou 36 0 0 01 Dec 2022
Synthetic data enable experiments in atomistic machine learning John L A Gardner Z. Beaulieu Volker L. Deringer 37 6 0 29 Nov 2022
Counterfactual Learning with Multioutput Deep Kernels A. Caron G. Baio I. Manolopoulou BDL CML OffRL 25 1 0 20 Nov 2022
Deep Gaussian Processes for Air Quality Inference Aadesh Desai Eshan Gujarathi Saagar Parikh Sachin Yadav Zeel B Patel Nipun Batra 36 2 0 18 Nov 2022
ET-AL: Entropy-Targeted Active Learning for Bias Mitigation in Materials Data Hengrui Zhang Wei Chen J. Rondinelli Wei Chen AI4CE 24 17 0 15 Nov 2022
Combining Multi-Fidelity Modelling and Asynchronous Batch Bayesian Optimization Jose Pablo Folch Robert M. Lee B. Shafei David Walz Calvin Tsay Mark van der Wilk Ruth Misener 41 23 0 11 Nov 2022
Online Stochastic Variational Gaussian Process Mapping for Large-Scale SLAM in Real Time Ignacio Torroba M. Chella Aldo Terán Niklas Rolleberg John Folkesson 22 1 0 10 Nov 2022
Optimizing Closed-Loop Performance with Data from Similar Systems: A Bayesian Meta-Learning Approach Ankush Chakrabarty 28 9 0 31 Oct 2022
Multi-Fidelity Bayesian Optimization with Unreliable Information Sources P. Mikkola Julien Martinelli Louis Filstroff Samuel Kaski 42 10 0 25 Oct 2022
Exploring Predictive Uncertainty and Calibration in NLP: A Study on the Impact of Method & Data Scarcity Dennis Ulmer J. Frellsen Christian Hardmeier 200 22 0 20 Oct 2022
Streaming PAC-Bayes Gaussian process regression with a performance guarantee for online decision making Tianyu Liu Jie Lu Zheng Yan Guangquan Zhang 49 0 0 16 Oct 2022
Numerically Stable Sparse Gaussian Processes via Minimum Separation using Cover Trees Alexander Terenin David R. Burt A. Artemev Seth Flaxman Mark van der Wilk C. Rasmussen Hong Ge 60 7 0 14 Oct 2022
Near-Optimal Multi-Agent Learning for Safe Coverage Control Manish Prajapat M. Turchetta Melanie Zeilinger Andreas Krause 35 14 0 12 Oct 2022
Efficient Gaussian Process Model on Class-Imbalanced Datasets for Generalized Zero-Shot Learning Changkun Ye Nick Barnes L. Petersson Russell Tsuchida BDL SyDa VLM 37 3 0 11 Oct 2022
Joint Entropy Search for Multi-objective Bayesian Optimization Ben Tu Axel Gandy N. Kantas B. Shafei 40 38 0 06 Oct 2022
Generalizing Bayesian Optimization with Decision-theoretic Entropies Willie Neiswanger Lantao Yu Shengjia Zhao Chenlin Meng Stefano Ermon UQCV 50 11 0 04 Oct 2022
Backflipping with Miniature Quadcopters by Gaussian Process Based Control and Planning Péter Antal Tamás Péni R. Tóth 45 8 0 29 Sep 2022
Multipoint-BAX: A New Approach for Efficiently Tuning Particle Accelerator Emittance via Virtual Objectives Sara Ayoub Miskovich Willie Neiswanger W. Colocho C. Emma Jacqueline Garrahan T. Maxwell C. Mayes Stefano Ermon A. Edelen Daniel Ratner 34 3 0 10 Sep 2022
Optimistic Optimization of Gaussian Process Samples Julia Grosse Cheng Zhang Philipp Hennig GP 18 0 0 02 Sep 2022
Time-Optimal Handover Trajectory Planning for Aerial Manipulators based on Discrete Mechanics and Complementarity Constraints Wei Luo Jingmin Chen Henrik Ebel P. Eberhard 19 12 0 01 Sep 2022
Automatic Identification of Coal and Rock/Gangue Based on DenseNet and Gaussian Process Yu-Feng Li 38 1 0 31 Aug 2022
Constraining Gaussian Processes to Systems of Linear Ordinary Differential Equations Andreas Besginow Markus Lange-Hegermann 37 11 0 26 Aug 2022
NeuralUQ: A comprehensive library for uncertainty quantification in neural differential equations and operators Zongren Zou Xuhui Meng Apostolos F. Psaros George Karniadakis AI4CE 36 37 0 25 Aug 2022
Fast emulation of density functional theory simulations using approximate Gaussian processes S. Stetzler M. Grosskopf E. Lawrence 23 0 0 24 Aug 2022
Event-Triggered Time-Varying Bayesian Optimization Paul Brunzema Alexander von Rohr Friedrich Solowjow Sebastian Trimpe 21 7 0 23 Aug 2022
Gaussian Process Surrogate Models for Neural Networks Michael Y. Li Erin Grant Thomas Griffiths BDL SyDa 43 7 0 11 Aug 2022
Bayesian Optimization with Informative Covariance Afonso Eduardo Michael U. Gutmann 29 3 0 04 Aug 2022
Doubly Deformable Aggregation of Covariance Matrices for Few-shot Segmentation Zhitong Xiong Haopeng Li Xiao Xiang Zhu 44 36 0 30 Jul 2022
On Controller Tuning with Time-Varying Bayesian Optimization Paul Brunzema Alexander von Rohr Sebastian Trimpe 34 17 0 22 Jul 2022