Zobrazeno 1 - 10
of 3 967
pro vyhledávání: '"Péter, I."'
Autor:
Tan, Samuel, Frazier, Peter I.
We consider the predict-then-optimize paradigm for decision-making in which a practitioner (1) trains a supervised learning model on historical data of decisions, contexts, and rewards, and then (2) uses the resulting model to make future binary deci
Externí odkaz:
http://arxiv.org/abs/2406.07866
We construct a fast, transferable, general purpose, machine-learning interatomic potential suitable for large-scale simulations of $N_2$. The potential is trained only on high quality quantum chemical molecule-molecule interactions, no condensed phas
Externí odkaz:
http://arxiv.org/abs/2405.05092
Autor:
Anderson, Richard I., Viviani, Giordano, Shetye, Shreeya S., Mowlavi, Nami, Eyer, Laurent, Palaversa, Lovro, Holl, Berry, Blanco-Cuaresma, Sergi, Kravchenko, Kateryna, Pawlak, Michał, Reyes, Mauricio Cruz, Khan, Saniya, Netzel, Henryka E., Löbling, Lisa, Pápics, Péter I., Postel, Andreas, Roelens, Maroussia, Spetsieri, Zoi T., Thoul, Anne, Zák, Jiří, Bonvin, Vivien, Martin, David V., Millon, Martin, Saesen, Sophie, Wyttenbach, Aurélien, Figueira, Pedro, Marmier, Maxime, Prins, Saskia, Raskin, Gert, van Winckel, Hans
Publikováno v:
A&A 686, A177 (2024)
This first VELOCE data release comprises 18,225 high-precision RV measurements of 258 bona fide classical Cepheids on both hemispheres collected mainly between 2010 and 2022, alongside 1161 additional observations of 164 other stars. The median per-o
Externí odkaz:
http://arxiv.org/abs/2404.12280
Autor:
Buathong, Poompol, Wan, Jiayue, Astudillo, Raul, Daulton, Samuel, Balandat, Maximilian, Frazier, Peter I.
Bayesian optimization is a powerful framework for optimizing functions that are expensive or time-consuming to evaluate. Recent work has considered Bayesian optimization of function networks (BOFN), where the objective function is given by a network
Externí odkaz:
http://arxiv.org/abs/2311.02146
During the COVID-19 pandemic, safely implementing in-person indoor instruction was a high priority for universities nationwide. To support this effort at the University, we developed a mathematical model for estimating the risk of SARS-CoV-2 transmis
Externí odkaz:
http://arxiv.org/abs/2310.04563
Autor:
Henriksen, Andreea I., Antoci, Victoria, Saio, Hideyuki, Grundahl, Frank, Kjeldsen, Hans, Van Reeth, Timothy, Bowman, Dominic M., Pápics, Péter I., De Cat, Peter, Krüger, Joachim, Andersen, M. Fredslund, Pallé, P. L.
Here we report an ensemble study of 214 A- and F-type stars observed by \textit{Kepler}, exhibiting the so-called \textit{hump and spike} periodic signal, explained by Rossby modes (r~modes) -- the \textit{hump} -- and magnetic stellar spots or overs
Externí odkaz:
http://arxiv.org/abs/2306.16766
Autor:
Salzbrenner, Pascal T., Joo, Se Hun, Conway, Lewis J., Cooke, Peter I. C., Zhu, Bonan, Matraszek, Milosz P., Witt, William C., Pickard, Chris J.
Publikováno v:
J. Chem. Phys. 159, 144801 (2023)
Machine-learned interatomic potentials are fast becoming an indispensable tool in computational materials science. One approach is the ephemeral data-derived potential (EDDP), which was designed to accelerate atomistic structure prediction. The EDDP
Externí odkaz:
http://arxiv.org/abs/2306.06475
Preferential Bayesian optimization (PBO) is a framework for optimizing a decision maker's latent utility function using preference feedback. This work introduces the expected utility of the best option (qEUBO) as a novel acquisition function for PBO.
Externí odkaz:
http://arxiv.org/abs/2303.15746
Autor:
Ogbebor, Jason, Valenza, John J., Ravikovitch, Peter I., Karunarathne, Ashoka, Muraro, Giovanni, Lebedev, Maxim, Gurevich, Boris, Khalizov, Alexei F., Gor, Gennady Y.
Publikováno v:
Phys. Rev. E, 2023, 108, 024802
Thermodynamic properties of fluids confined in nanopores differ from those observed in the bulk. To investigate the effect of nanoconfinement on water compressibility, we performed water sorption experiments on two nanoporous glass samples while conc
Externí odkaz:
http://arxiv.org/abs/2303.12193
In many applications of online decision making, the environment is non-stationary and it is therefore crucial to use bandit algorithms that handle changes. Most existing approaches are designed to protect against non-smooth changes, constrained only
Externí odkaz:
http://arxiv.org/abs/2301.12366