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

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

28 September 2018
Jacob R. Gardner
Geoff Pleiss
D. Bindel
Kilian Q. Weinberger
A. Wilson
    GP
ArXivPDFHTML

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

50 / 207 papers shown
Title
Bidirectional Information Flow (BIF) -- A Sample Efficient Hierarchical Gaussian Process for Bayesian Optimization
Bidirectional Information Flow (BIF) -- A Sample Efficient Hierarchical Gaussian Process for Bayesian Optimization
Juan D. Guerra
Thomas Garbay
Guillaume Lajoie
Marco Bonizzato
11
0
0
16 May 2025
Scalable Computations for Generalized Mixed Effects Models with Crossed Random Effects Using Krylov Subspace Methods
Scalable Computations for Generalized Mixed Effects Models with Crossed Random Effects Using Krylov Subspace Methods
Pascal Kündig
Fabio Sigrist
29
0
0
14 May 2025
Finite-Sample-Based Reachability for Safe Control with Gaussian Process Dynamics
Finite-Sample-Based Reachability for Safe Control with Gaussian Process Dynamics
Manish Prajapat
Johannes Köhler
Amon Lahr
Andreas Krause
Melanie Zeilinger
38
0
0
12 May 2025
GPRat: Gaussian Process Regression with Asynchronous Tasks
GPRat: Gaussian Process Regression with Asynchronous Tasks
Maksim Helmann
Alexander Strack
Dirk Pflüger
GP
43
0
0
30 Apr 2025
On learning functions over biological sequence space: relating Gaussian process priors, regularization, and gauge fixing
On learning functions over biological sequence space: relating Gaussian process priors, regularization, and gauge fixing
Samantha Petti
Carlos Martí-Gómez
Justin B. Kinney
Juannan Zhou
David M. McCandlish
GP
29
0
0
26 Apr 2025
The Power of the Pareto Front: Balancing Uncertain Rewards for Adaptive Experimentation in scanning probe microscopy
The Power of the Pareto Front: Balancing Uncertain Rewards for Adaptive Experimentation in scanning probe microscopy
Yu Liu
Sergei V. Kalinin
38
0
0
09 Apr 2025
GOLLuM: Gaussian Process Optimized LLMs -- Reframing LLM Finetuning through Bayesian Optimization
GOLLuM: Gaussian Process Optimized LLMs -- Reframing LLM Finetuning through Bayesian Optimization
Bojana Ranković
P. Schwaller
BDL
276
0
0
08 Apr 2025
Preconditioned Additive Gaussian Processes with Fourier Acceleration
Preconditioned Additive Gaussian Processes with Fourier Acceleration
Theresa Wagner
Tianshi Xu
Franziska Nestler
Yuanzhe Xi
Martin Stoll
69
1
0
01 Apr 2025
Constrained multi-fidelity Bayesian optimization with automatic stop condition
Constrained multi-fidelity Bayesian optimization with automatic stop condition
Zahra Zanjani Foumani
Ramin Bostanabad
76
0
0
03 Mar 2025
Position: Curvature Matrices Should Be Democratized via Linear Operators
Position: Curvature Matrices Should Be Democratized via Linear Operators
Felix Dangel
Runa Eschenhagen
Weronika Ormaniec
Andres Fernandez
Lukas Tatzel
Agustinus Kristiadi
69
3
0
31 Jan 2025
Covering Multiple Objectives with a Small Set of Solutions Using Bayesian Optimization
Covering Multiple Objectives with a Small Set of Solutions Using Bayesian Optimization
Natalie Maus
Kyurae Kim
Yimeng Zeng
Haydn Thomas Jones
Fangping Wan
Marcelo Der Torossian Torres
Cesar de la Fuente-Nunez
Jacob R. Gardner
95
0
0
31 Jan 2025
Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning
Real-Time Generation of Near-Minimum-Energy Trajectories via Constraint-Informed Residual Learning
Domenico Dona'
Giovanni Franzese
Cosimo Della Santina
Paolo Boscariol
Basilio Lenzo
52
0
0
17 Jan 2025
Evaluation of uncertainty estimations for Gaussian process regression based machine learning interatomic potentials
Evaluation of uncertainty estimations for Gaussian process regression based machine learning interatomic potentials
Matthias Holzenkamp
Dongyu Lyu
Ulrich Kleinekathöfer
Peter Zaspel
42
0
0
10 Jan 2025
Practical Performative Policy Learning with Strategic Agents
Practical Performative Policy Learning with Strategic Agents
Qianyi Chen
Ying Chen
Bo Li
115
0
0
02 Dec 2024
Constrained composite Bayesian optimization for rational synthesis of polymeric particles
Constrained composite Bayesian optimization for rational synthesis of polymeric particles
Fanjin Wang
Maryam Parhizkar
Anthony Harker
Mohan Edirisinghe
31
0
0
06 Nov 2024
Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models
Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models
Jinlin Lai
Justin Domke
Daniel Sheldon
43
0
0
31 Oct 2024
High-Dimensional Gaussian Process Regression with Soft Kernel Interpolation
High-Dimensional Gaussian Process Regression with Soft Kernel Interpolation
Chris Camaño
Daniel Huang
BDL
GP
50
1
0
28 Oct 2024
MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning
MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning
Peter Eckmann
D. Wu
G. Heinzelmann
Michael K. Gilson
Rose Yu
AI4CE
49
0
0
15 Oct 2024
Scaling Gaussian Processes for Learning Curve Prediction via Latent
  Kronecker Structure
Scaling Gaussian Processes for Learning Curve Prediction via Latent Kronecker Structure
Jihao Andreas Lin
Sebastian Ament
Maximilian Balandat
E. Bakshy
BDL
31
2
0
11 Oct 2024
Gridded Transformer Neural Processes for Large Unstructured
  Spatio-Temporal Data
Gridded Transformer Neural Processes for Large Unstructured Spatio-Temporal Data
Matthew Ashman
Cristiana-Diana Diaconu
Eric Langezaal
Adrian Weller
Richard E. Turner
AI4TS
41
1
0
09 Oct 2024
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling
Jasmine Bayrooti
Carl Henrik Ek
Amanda Prorok
50
0
0
07 Oct 2024
Embrace rejection: Kernel matrix approximation by accelerated randomly pivoted Cholesky
Embrace rejection: Kernel matrix approximation by accelerated randomly pivoted Cholesky
Ethan N. Epperly
J. Tropp
R. Webber
36
4
0
04 Oct 2024
Constraining Gaussian Process Implicit Surfaces for Robot Manipulation
  via Dataset Refinement
Constraining Gaussian Process Implicit Surfaces for Robot Manipulation via Dataset Refinement
Abhinav Kumar
Peter Mitrano
Dmitry Berenson
37
0
0
30 Sep 2024
Autonomous Wheel Loader Navigation Using Goal-Conditioned Actor-Critic MPC
Autonomous Wheel Loader Navigation Using Goal-Conditioned Actor-Critic MPC
Aleksi Mäki-Penttilä
Naeim Ebrahimi Toulkani
Reza Ghabcheloo
39
0
0
24 Sep 2024
Conformal Prediction for Manifold-based Source Localization with Gaussian Processes
Conformal Prediction for Manifold-based Source Localization with Gaussian Processes
Vadim Rozenfeld
Bracha Laufer Goldshtein
40
0
0
18 Sep 2024
Towards safe and tractable Gaussian process-based MPC: Efficient
  sampling within a sequential quadratic programming framework
Towards safe and tractable Gaussian process-based MPC: Efficient sampling within a sequential quadratic programming framework
Manish Prajapat
Amon Lahr
Johannes Köhler
Andreas Krause
Melanie Zeilinger
37
2
0
13 Sep 2024
Bayesian Optimization for Non-Convex Two-Stage Stochastic Optimization Problems
Bayesian Optimization for Non-Convex Two-Stage Stochastic Optimization Problems
Jack M. Buckingham
Ivo Couckuyt
Juergen Branke
48
0
0
30 Aug 2024
Batch Active Learning in Gaussian Process Regression using Derivatives
Batch Active Learning in Gaussian Process Regression using Derivatives
Hon Sum Alec Yu
Christoph Zimmer
D. Nguyen-Tuong
GP
31
1
0
03 Aug 2024
Smooth Path Planning Using a Gaussian Process Regression Map for Mobile
  Robot Navigation
Smooth Path Planning Using a Gaussian Process Regression Map for Mobile Robot Navigation
Quentin Serdel
J. Marzat
Julien Moras
GP
23
1
0
08 Jul 2024
Adaptive RKHS Fourier Features for Compositional Gaussian Process Models
Adaptive RKHS Fourier Features for Compositional Gaussian Process Models
Xinxing Shi
Thomas Baldwin-McDonald
Mauricio A. Álvarez
82
0
0
01 Jul 2024
MUSE-Net: Missingness-aware mUlti-branching Self-attention Encoder for Irregular Longitudinal Electronic Health Records
MUSE-Net: Missingness-aware mUlti-branching Self-attention Encoder for Irregular Longitudinal Electronic Health Records
Zekai Wang
Tieming Liu
B. Yao
57
0
0
30 Jun 2024
Data-driven identification of port-Hamiltonian DAE systems by Gaussian
  processes
Data-driven identification of port-Hamiltonian DAE systems by Gaussian processes
Peter Zaspel
Michael Günther
39
2
0
26 Jun 2024
A survey and benchmark of high-dimensional Bayesian optimization of
  discrete sequences
A survey and benchmark of high-dimensional Bayesian optimization of discrete sequences
Miguel González Duque
Richard Michael
Simon Bartels
Yevgen Zainchkovskyy
Søren Hauberg
Wouter Boomsma
49
4
0
07 Jun 2024
Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes
Improving Linear System Solvers for Hyperparameter Optimisation in Iterative Gaussian Processes
J. Lin
Shreyas Padhy
Bruno Mlodozeniec
Javier Antorán
José Miguel Hernández-Lobato
46
2
0
28 May 2024
Gradients of Functions of Large Matrices
Gradients of Functions of Large Matrices
Nicholas Krämer
Pablo Moreno-Muñoz
Hrittik Roy
Søren Hauberg
40
0
0
27 May 2024
CMA-ES for Safe Optimization
CMA-ES for Safe Optimization
Kento Uchida
Ryoki Hamano
Masahiro Nomura
Shota Saito
Shinichi Shirakawa
37
1
0
17 May 2024
Future Aware Safe Active Learning of Time Varying Systems using Gaussian Processes
Future Aware Safe Active Learning of Time Varying Systems using Gaussian Processes
Markus Lange-Hegermann
Christoph Zimmer
AI4TS
47
0
0
17 May 2024
Kermut: Composite kernel regression for protein variant effects
Kermut: Composite kernel regression for protein variant effects
Peter Mørch Groth
Mads Herbert Kerrn
Lars Olsen
Jesper Salomon
Wouter Boomsma
47
2
0
09 Apr 2024
Spatio-Temporal Attention and Gaussian Processes for Personalized Video
  Gaze Estimation
Spatio-Temporal Attention and Gaussian Processes for Personalized Video Gaze Estimation
Swati Jindal
Mohit Yadav
Roberto Manduchi
37
5
0
08 Apr 2024
Learning Piecewise Residuals of Control Barrier Functions for Safety of
  Switching Systems using Multi-Output Gaussian Processes
Learning Piecewise Residuals of Control Barrier Functions for Safety of Switching Systems using Multi-Output Gaussian Processes
Mohammad Aali
Jun Liu
37
0
0
26 Mar 2024
Multi-Fidelity Bayesian Optimization With Across-Task Transferable Max-Value Entropy Search
Multi-Fidelity Bayesian Optimization With Across-Task Transferable Max-Value Entropy Search
Yunchuan Zhang
Sangwoo Park
Osvaldo Simeone
48
5
0
14 Mar 2024
Gradient-enhanced deep Gaussian processes for multifidelity modelling
Gradient-enhanced deep Gaussian processes for multifidelity modelling
Viv Bone
Chris van der Heide
Kieran Mackle
Ingo Jahn
P. Dower
Chris Manzie
27
1
0
25 Feb 2024
Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders
Effective Bayesian Causal Inference via Structural Marginalisation and Autoregressive Orders
Christian Toth
Christian Knoll
Franz Pernkopf
Robert Peharz
CML
59
1
0
22 Feb 2024
Enhancing predictive capabilities in fusion burning plasmas through
  surrogate-based optimization in core transport solvers
Enhancing predictive capabilities in fusion burning plasmas through surrogate-based optimization in core transport solvers
P. Rodriguez-Fernandez
N. T. Howard
A. Saltzman
S. Kantamneni
J. Candy
C. Holland
M. Balandat
Sebastian Ament
A. E. White
20
10
0
19 Dec 2023
Towards Safe Multi-Task Bayesian Optimization
Towards Safe Multi-Task Bayesian Optimization
Jannis O. Lübsen
Christian Hespe
Annika Eichler
29
3
0
12 Dec 2023
Practical Path-based Bayesian Optimization
Practical Path-based Bayesian Optimization
Jose Pablo Folch
J. Odgers
Shiqiang Zhang
Robert M. Lee
B. Shafei
David Walz
Calvin Tsay
Mark van der Wilk
Ruth Misener
49
2
0
01 Dec 2023
A systematic study comparing hyperparameter optimization engines on
  tabular data
A systematic study comparing hyperparameter optimization engines on tabular data
Balazs Kegl
28
1
0
27 Nov 2023
Robust and Conjugate Gaussian Process Regression
Robust and Conjugate Gaussian Process Regression
Matias Altamirano
F. Briol
Jeremias Knoblauch
35
10
0
01 Nov 2023
Implicit Manifold Gaussian Process Regression
Implicit Manifold Gaussian Process Regression
Bernardo Fichera
Viacheslav Borovitskiy
Andreas Krause
A. Billard
20
3
0
30 Oct 2023
Pseudo-Bayesian Optimization
Pseudo-Bayesian Optimization
Haoxian Chen
Henry Lam
34
2
0
15 Oct 2023
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