Zobrazeno 1 - 10
of 11 285
pro vyhledávání: '"Niño, P."'
The higher-rank numerical range is a convex compact set generalizing the classical numerical range of a square complex matrix, first appearing in the study of quantum error correction. We will discuss some of the real algebraic and convex geometry of
Externí odkaz:
http://arxiv.org/abs/2410.21625
Autor:
Meulemans, Alexander, Kobayashi, Seijin, von Oswald, Johannes, Scherrer, Nino, Elmoznino, Eric, Richards, Blake, Lajoie, Guillaume, Arcas, Blaise Agüera y, Sacramento, João
Self-interested individuals often fail to cooperate, posing a fundamental challenge for multi-agent learning. How can we achieve cooperation among self-interested, independent learning agents? Promising recent work has shown that in certain tasks coo
Externí odkaz:
http://arxiv.org/abs/2410.18636
A nut graph is a simple graph for which the adjacency matrix has a single zero eigenvalue such that all non-zero kernel eigenvectors have no zero entry. It is known that infinitely many $d$-regular nut graphs exist for $3 \leq d \leq 12$ and for $d \
Externí odkaz:
http://arxiv.org/abs/2410.14063
Because of their conveniently tunable optoelectronic properties, semiconductor nanocrystals have become established components for new devices and emergent technologies, in a broad range of applications which include agriculture, medicine, energy har
Externí odkaz:
http://arxiv.org/abs/2409.19809
In stochastic multi-factor commodity models, it is often the case that futures prices are explained by two latent state variables which represent the short and long term stochastic factors. In this work, we develop the family of stochastic models usi
Externí odkaz:
http://arxiv.org/abs/2409.19386
PDSim is an R package that enables users to simulate commodity futures prices using the polynomial diffusion model introduced in Filipovic and Larsson (2016) through both a Shiny web application and R scripts. It also provides state variables and con
Externí odkaz:
http://arxiv.org/abs/2409.19385
Autor:
Bacheva, Vesna, Madison, Imani, Baldwin, Mathew, Beilstein, Mark, Call, Douglas F., Deaver, Jessica A., Efimenko, Kirill, Genzer, Jan, Grieger, Khara, Gu, April Z., Ilman, Mehmet Mert, Liu, Jen, Li, Sijin, Mayer, Brooke K., Mishra, Anand Kumar, Nino, Juan Claudio, Rubambiza, Gloire, Sengers, Phoebe, Shepherd, Robert, Woodson, Jesse, Weatherspoon, Hakim, Frank, Margaret, Jones, Jacob, Sozzani, Rosangela, Stroock, Abraham
Feeding the growing human population sustainably amidst climate change is one of the most important challenges in the 21st century. Current practices often lead to the overuse of agronomic inputs, such as synthetic fertilizers and water, resulting in
Externí odkaz:
http://arxiv.org/abs/2409.12337
Autor:
Kuijf, Ilse S., Tromp, Willem O., Benschop, Tjerk, Ramones, Niño Philip, Sulangi, Miguel Antonio, van Nieuwenburg, Evert P. L., Allan, Milan P.
Tunneling spectroscopy is an important tool for the study of both real-space and momentum-space electronic structure of correlated electron systems. However, such measurements often yield noisy data. Machine learning provides techniques to reduce the
Externí odkaz:
http://arxiv.org/abs/2409.08891
Autor:
Rovirola, Marc, Khaliq, M. Waqas, Casals, Blai, Begué, Adrian, Biskup, Neven, Coton, Noelia, Hernàndez, Joan Manel, Niño, Miguel Angel, Foerster, Michael, Hernández-Mínguez, Alberto, Ranchal, Rocío, Costache, Marius V., García-Santiago, Antoni, Macià, Ferran
The interaction between surface acoustic waves and magnetization offers an efficient route for electrically controlling magnetic states. Here, we demonstrate the excitation of magnetoacoustic waves in galfenol, a highly magnetostrictive alloy made of
Externí odkaz:
http://arxiv.org/abs/2409.04370
Autor:
Wulfmeier, Markus, Bloesch, Michael, Vieillard, Nino, Ahuja, Arun, Bornschein, Jorg, Huang, Sandy, Sokolov, Artem, Barnes, Matt, Desjardins, Guillaume, Bewley, Alex, Bechtle, Sarah Maria Elisabeth, Springenberg, Jost Tobias, Momchev, Nikola, Bachem, Olivier, Geist, Matthieu, Riedmiller, Martin
The majority of language model training builds on imitation learning. It covers pretraining, supervised fine-tuning, and affects the starting conditions for reinforcement learning from human feedback (RLHF). The simplicity and scalability of maximum
Externí odkaz:
http://arxiv.org/abs/2409.01369