Zobrazeno 1 - 10
of 51 533
pro vyhledávání: '"Haber AS"'
Model-based reinforcement learning (MBRL) is a promising route to sample-efficient policy optimization. However, a known vulnerability of reconstruction-based MBRL consists of scenarios in which detailed aspects of the world are highly predictable, b
Externí odkaz:
http://arxiv.org/abs/2412.05766
Autor:
Ahamed, Shadab, Haber, Eldad
Inverse problems, which involve estimating parameters from incomplete or noisy observations, arise in various fields such as medical imaging, geophysics, and signal processing. These problems are often ill-posed, requiring regularization techniques t
Externí odkaz:
http://arxiv.org/abs/2412.04766
Autor:
Chan, Yang-hao, Haber, Jonah B., Naik, Mit H., Louie, Steven G., Neaton, Jeffrey B., da Jornada, Felipe H., Qiu, Diana Y.
Understanding exciton thermalization is critical for optimizing optoelectronic and photocatalytic processes in many materials. However, it is hard to access the dynamics of such processes experimentally, especially on systems such as monolayer transi
Externí odkaz:
http://arxiv.org/abs/2412.04001
Developing problem-solving competency is central to Science, Technology, Engineering, and Mathematics (STEM) education, yet translating this priority into effective approaches to problem-solving instruction and assessment remain a significant challen
Externí odkaz:
http://arxiv.org/abs/2412.02653
Autor:
Sun, Fan-Yun, Liu, Weiyu, Gu, Siyi, Lim, Dylan, Bhat, Goutam, Tombari, Federico, Li, Manling, Haber, Nick, Wu, Jiajun
Open-universe 3D layout generation arranges unlabeled 3D assets conditioned on language instruction. Large language models (LLMs) struggle with generating physically plausible 3D scenes and adherence to input instructions, particularly in cluttered s
Externí odkaz:
http://arxiv.org/abs/2412.02193
Autor:
Klieger, Benjamin, Charitsis, Charis, Suzara, Miroslav, Wang, Sierra, Haber, Nick, Mitchell, John C.
We explore the potential for productive team-based collaboration between humans and Artificial Intelligence (AI) by presenting and conducting initial tests with a general framework that enables multiple human and AI agents to work together as peers.
Externí odkaz:
http://arxiv.org/abs/2412.01992
We examine the correlations between new scalar boson decays to photons and electric dipole moments (EDMs) in the CP-violating flavor-aligned two-Higgs-doublet model (2HDM). It is convenient to work in the Higgs basis $\{{H}_1, {H}_2\}$ where only the
Externí odkaz:
http://arxiv.org/abs/2412.00523
Autor:
Bercovich, Akhiad, Ronen, Tomer, Abramovich, Talor, Ailon, Nir, Assaf, Nave, Dabbah, Mohammad, Galil, Ido, Geifman, Amnon, Geifman, Yonatan, Golan, Izhak, Haber, Netanel, Karpas, Ehud, Koren, Roi, Levy, Itay, Molchanov, Pavlo, Mor, Shahar, Moshe, Zach, Nabwani, Najeeb, Puny, Omri, Rubin, Ran, Schen, Itamar, Shahaf, Ido, Tropp, Oren, Argov, Omer Ullman, Zilberstein, Ran, El-Yaniv, Ran
Large language models (LLMs) have demonstrated remarkable capabilities, but their adoption is limited by high computational costs during inference. While increasing parameter counts enhances accuracy, it also widens the gap between state-of-the-art c
Externí odkaz:
http://arxiv.org/abs/2411.19146
Understanding and predicting complex dynamics in accelerators is necessary for their successful operation. A grand challenge in accelerator physics is to develop predictive virtual accelerators that mitigate design cost and schedule risk. Data-driven
Externí odkaz:
http://arxiv.org/abs/2410.14019
Autor:
Sun, Fan-Yun, Harini, S. I., Yi, Angela, Zhou, Yihan, Zook, Alex, Tremblay, Jonathan, Cross, Logan, Wu, Jiajun, Haber, Nick
Generating simulations to train intelligent agents in game-playing and robotics from natural language input, from user input or task documentation, remains an open-ended challenge. Existing approaches focus on parts of this challenge, such as generat
Externí odkaz:
http://arxiv.org/abs/2409.17652