Zobrazeno 1 - 10
of 50 262
pro vyhledávání: '"Kagan AN"'
Autor:
Tanveer, Md Sayed, Patel, Dhruvik, Schweiger, Hunter E., Abu-Bonsrah, Kwaku Dad, Watmuff, Brad, Azadi, Azin, Pryshchep, Sergey, Narayanan, Karthikeyan, Puleo, Christopher, Natarajan, Kannathal, Mostajo-Radji, Mohammed A., Kagan, Brett J., Wang, Ge
With the recent advancements in artificial intelligence, researchers and industries are deploying gigantic models trained on billions of samples. While training these models consumes a huge amount of energy, human brains produce similar outputs (alon
Externí odkaz:
http://arxiv.org/abs/2412.14112
High-energy physics requires the generation of large numbers of simulated data samples from complex but analytically tractable distributions called matrix elements. Surrogate models, such as normalizing flows, are gaining popularity for this task due
Externí odkaz:
http://arxiv.org/abs/2411.16234
In this study, we analyze the dielectric function of high-Tc cuprates as a function of doping level, taking into account the full energy band dispersion within the CuO$_2$ monolayer. In addition to the conventional two-dimensional (2D) gapless plasmo
Externí odkaz:
http://arxiv.org/abs/2411.12836
A number of models have been developed for information spread through networks, often for solving the Influence Maximization (IM) problem. IM is the task of choosing a fixed number of nodes to "seed" with information in order to maximize the spread o
Externí odkaz:
http://arxiv.org/abs/2411.09100
Autor:
Marino, Emanuele, LaCour, R. Allen, Moore, Timothy C., van Dongen, Sjoerd W., Keller, Austin W., An, Di, Yang, Shengsong, Rosen, Daniel J., Gouget, Guillaume, Tsai, Esther H. R., Kagan, Cherie R., Kodger, Thomas E., Glotzer, Sharon C., Murray, Christopher B.
Publikováno v:
Nature Synthesis 3, 111-122, 2024
The synthesis of binary nanocrystal superlattices (BNSLs) enables the targeted integration of orthogonal physical properties, like photoluminescence and magnetism, into a single superstructure, unlocking a vast design space for multifunctional materi
Externí odkaz:
http://arxiv.org/abs/2410.17016
Autor:
Kagan, Alexis
We consider the range $R^{(n)}$, the tree made up of visited vertices by a diffusive null-recurrent randomly biased walk $\mathbb{X}$ on a Galton-Watson tree $\mathbb{T}$ up to the $n$-th return time to its root and we consider the following genealog
Externí odkaz:
http://arxiv.org/abs/2410.08402
We introduce Temporal Attention-enhanced Variational Graph Recurrent Neural Network (TAVRNN), a novel framework for analyzing the evolving dynamics of neuronal connectivity networks in response to external stimuli and behavioral feedback. TAVRNN capt
Externí odkaz:
http://arxiv.org/abs/2410.00665
We explored the efficacy of lab-grown diamonds as potential target materials for the direct detection of sub-GeV dark matter~(DM) using metallic magnetic calorimeters~(MMCs). Diamond, with its excellent phononic properties and the low atomic mass of
Externí odkaz:
http://arxiv.org/abs/2409.19238
Autor:
Kagan, Alexis, Véchambre, Grégoire
We define a family of continuous-time branching particle systems on the non-negative real line called branching subordinators and closely related to branching L\'evy processes introduced by Bertoin and Mallein arXiv:1703.08078. We pay a particular at
Externí odkaz:
http://arxiv.org/abs/2409.16617
Autor:
Leigh, Matthew, Klein, Samuel, Charton, François, Golling, Tobias, Heinrich, Lukas, Kagan, Michael, Ochoa, Inês, Osadchy, Margarita
In this work, we significantly enhance masked particle modeling (MPM), a self-supervised learning scheme for constructing highly expressive representations of unordered sets relevant to developing foundation models for high-energy physics. In MPM, a
Externí odkaz:
http://arxiv.org/abs/2409.12589