Emulation of physical processes with Emukit

25 October 2021

Papers citing "Emulation of physical processes with Emukit"

44 / 44 papers shown

Title
Scalable Meta-Learning with Gaussian Processes Petru Tighineanu Lukas Großberger P. Baireuther Kathrin Skubch Stefan Falkner Julia Vinogradska Felix Berkenkamp 34 4 0 01 Dec 2023
Adaptive importance sampling for heavy-tailed distributions via $α$ -divergence minimization Thomas Guilmeau Nicola Branchini Émilie Chouzenoux Victor Elvira 44 2 0 25 Oct 2023
AutoML in Heavily Constrained Applications Felix Neutatz Marius Lindauer Ziawasch Abedjan 25 4 0 29 Jun 2023
Framework and Benchmarks for Combinatorial and Mixed-variable Bayesian Optimization Kamil Dreczkowski Antoine Grosnit Haitham Bou-Ammar 26 7 0 16 Jun 2023
Bayesian Numerical Integration with Neural Networks Katharina Ott Michael Tiemann Philipp Hennig F. Briol BDL 22 3 0 22 May 2023
Reproducibility Requires Consolidated Artifacts Iordanis Fostiropoulos Bowman Brown Laurent Itti AI4CE 14 1 0 21 May 2023
PyVBMC: Efficient Bayesian inference in Python Bobby Huggins Chengkun Li Marlon Tobaben Mikko J. Aarnos Luigi Acerbi 28 9 0 16 Mar 2023
Trieste: Efficiently Exploring The Depths of Black-box Functions with TensorFlow Victor Picheny Joel Berkeley Henry B. Moss Hrvoje Stojić Uri Granta ... Sergio Pascual-Diaz Stratis Markou Jixiang Qing Nasrulloh Loka Ivo Couckuyt 26 17 0 16 Feb 2023
Real-world Machine Learning Systems: A survey from a Data-Oriented Architecture Perspective Christian Cabrera Andrei Paleyes Pierre Thodoroff Neil D. Lawrence AI4TS AI4CE OOD 30 6 0 09 Feb 2023
Deep Gaussian Process-based Multi-fidelity Bayesian Optimization for Simulated Chemical Reactors Tom Savage N. Basha Omar K. Matar Ehecatl Antonio del Rio Chanona AI4CE 16 5 0 31 Oct 2022
An Active Learning Reliability Method for Systems with Partially Defined Performance Functions Jonathan Sadeghi Romain Mueller John Redford 10 2 0 05 Oct 2022
Optimistic Optimization of Gaussian Process Samples Julia Grosse Cheng Zhang Philipp Hennig GP 16 0 0 02 Sep 2022
Open Source Vizier: Distributed Infrastructure and API for Reliable and Flexible Blackbox Optimization Xingyou Song Sagi Perel Chansoo Lee Greg Kochanski Daniel Golovin 33 26 0 27 Jul 2022
Modeling the Machine Learning Multiverse Samuel J. Bell Onno P. Kampman Jesse Dodge Neil D. Lawrence 23 17 0 13 Jun 2022
$π$ BO: Augmenting Acquisition Functions with User Beliefs for Bayesian Optimization Carl Hvarfner Daniel Stoll Artur L. F. Souza Marius Lindauer Frank Hutter Luigi Nardi 15 68 0 23 Apr 2022
Machine Learning Simulates Agent-Based Model Towards Policy Bernardo Alves Furtado G. Andreão 15 0 0 04 Mar 2022
Uncertainty Aware System Identification with Universal Policies B. L. Semage Thommen George Karimpanal Santu Rana Svetha Venkatesh 18 3 0 11 Feb 2022
Fast Model-based Policy Search for Universal Policy Networks B. L. Semage Thommen George Karimpanal Santu Rana Svetha Venkatesh 27 1 0 11 Feb 2022
ProbNum: Probabilistic Numerics in Python Jonathan Wenger Nicholas Kramer Marvin Pfortner Jonathan Schmidt Nathanael Bosch ... A. Gessner Toni Karvonen F. Briol Maren Mahsereci Philipp Hennig 54 17 0 03 Dec 2021
Invariant Priors for Bayesian Quadrature Masha Naslidnyk Javier I. González Maren Mahsereci 13 2 0 02 Dec 2021
Transfer Learning with Gaussian Processes for Bayesian Optimization Petru Tighineanu Kathrin Skubch P. Baireuther Attila Reiss Felix Berkenkamp Julia Vinogradska 16 32 0 22 Nov 2021
GaussED: A Probabilistic Programming Language for Sequential Experimental Design Matthew A. Fisher Onur Teymur Chris J. Oates 40 1 0 15 Oct 2021
Graph Neural Network Guided Local Search for the Traveling Salesperson Problem Benjamin H. Hudson Qingbiao Li Matthew Malencia Amanda Prorok 33 63 0 11 Oct 2021
Machine Learning with Knowledge Constraints for Process Optimization of Open-Air Perovskite Solar Cell Manufacturing Zhe Liu Nicholas Rolston Austin C. Flick T. Colburn Zekun Ren R. Dauskardt Tonio Buonassisi 32 116 0 01 Oct 2021
Sonic: A Sampling-based Online Controller for Streaming Applications Yan Pei K. Pingali 34 0 0 15 Aug 2021
Computationally-Efficient Climate Predictions using Multi-Fidelity Surrogate Modelling Benoît Hudson F.P.J. Nijweide Isaac Sebenius AI4Cl AI4CE 14 1 0 03 Aug 2021
Bayesian Optimization is Superior to Random Search for Machine Learning Hyperparameter Tuning: Analysis of the Black-Box Optimization Challenge 2020 Ryan Turner David Eriksson M. McCourt J. Kiili Eero Laaksonen Zhen Xu Isabelle M Guyon BDL 30 289 0 20 Apr 2021
Residual Gaussian Process: A Tractable Nonparametric Bayesian Emulator for Multi-fidelity Simulations Wei W. Xing A. Shah Peng Wang Shandian Zhe Robert M. Kirby 22 12 0 08 Apr 2021
GIBBON: General-purpose Information-Based Bayesian OptimisatioN Henry B. Moss David S. Leslie Javier I. González Paul Rayson 26 43 0 05 Feb 2021
Optimised one-class classification performance O. Lenz Daniel Peralta Chris Cornelis 20 3 0 04 Feb 2021
Good practices for Bayesian Optimization of high dimensional structured spaces E. Siivola Javier I. González Andrei Paleyes Aki Vehtari 30 37 0 31 Dec 2020
Detection of Lexical Stress Errors in Non-Native (L2) English with Data Augmentation and Attention Daniel Korzekwa Roberto Barra-Chicote Szymon Zaporowski Grzegorz Beringer Jaime Lorenzo-Trueba Alicja Serafinowicz J. Droppo Thomas Drugman B. Kostek 15 9 0 29 Dec 2020
Amazon SageMaker Automatic Model Tuning: Scalable Gradient-Free Optimization Valerio Perrone Huibin Shen Aida Zolic I. Shcherbatyi Amr Ahmed ... Barbara Pogorzelska Miroslav Miladinovic K. Kenthapadi Matthias Seeger Cédric Archambeau 45 16 0 15 Dec 2020
Multi-fidelity data fusion for the approximation of scalar functions with low intrinsic dimensionality through active subspaces F. Romor M. Tezzele G. Rozza 12 4 0 16 Oct 2020
Asynchronous ε-Greedy Bayesian Optimisation George De Ath Richard Everson J. Fieldsend 35 5 0 15 Oct 2020
BOSS: Bayesian Optimization over String Spaces Henry B. Moss Daniel Beck Javier I. González David S. Leslie Paul Rayson 11 68 0 02 Oct 2020
Resource Aware Multifidelity Active Learning for Efficient Optimization Francesco Grassi Giorgio Manganini Michele Garraffa L. Mainini 14 6 0 09 Jul 2020
BOSH: Bayesian Optimization by Sampling Hierarchically Henry B. Moss David S. Leslie Paul Rayson 14 8 0 02 Jul 2020
Overview of Gaussian process based multi-fidelity techniques with variable relationship between fidelities Loïc Brevault M. Balesdent Ali Hebbal 24 69 0 30 Jun 2020
Multi-fidelity modeling with different input domain definitions using Deep Gaussian Processes Ali Hebbal Loïc Brevault M. Balesdent El-Ghazali Talbi N. Melab AI4CE 19 36 0 29 Jun 2020
Bayesian Optimization with a Prior for the Optimum Artur L. F. Souza Luigi Nardi Leonardo B. Oliveira K. Olukotun Marius Lindauer Frank Hutter 21 8 0 25 Jun 2020
MUMBO: MUlti-task Max-value Bayesian Optimization Henry B. Moss David S. Leslie Paul Rayson 23 33 0 22 Jun 2020
Conditional Deep Gaussian Processes: multi-fidelity kernel learning Chi-Ken Lu Patrick Shafto 19 5 0 07 Feb 2020
BOFFIN TTS: Few-Shot Speaker Adaptation by Bayesian Optimization Henry B. Moss Vatsal Aggarwal N. Prateek Javier I. González Roberto Barra-Chicote BDL 8 57 0 04 Feb 2020