Zobrazeno 1 - 10
of 13 500
pro vyhledávání: '"Ofir, A"'
We use PyDynamicaLC, a model using the least number of, and the least correlated, degrees of freedom needed to derive a photodynamical model, to describe some of the smallest -- and lowest TTV (transit timing variations) amplitude -- of the Kepler pl
Externí odkaz:
http://arxiv.org/abs/2410.11401
We present an inference scheme of long timescale, non-exponential kinetics from Molecular Dynamics simulations accelerated by stochastic resetting. Standard simulations provide valuable insight into chemical processes but are limited to timescales sh
Externí odkaz:
http://arxiv.org/abs/2410.09805
Autor:
Yang, John, Jimenez, Carlos E., Zhang, Alex L., Lieret, Kilian, Yang, Joyce, Wu, Xindi, Press, Ori, Muennighoff, Niklas, Synnaeve, Gabriel, Narasimhan, Karthik R., Yang, Diyi, Wang, Sida I., Press, Ofir
Autonomous systems for software engineering are now capable of fixing bugs and developing features. These systems are commonly evaluated on SWE-bench (Jimenez et al., 2024a), which assesses their ability to solve software issues from GitHub repositor
Externí odkaz:
http://arxiv.org/abs/2410.03859
Autor:
Roy, Rhombik, Alon, Ofir E.
Bosonic Josephson junctions provide a versatile platform for exploring quantum tunneling and coherence phenomena in ultracold atomic systems. While extensive research has examined the Josephson-junction dynamics in various double-well configurations,
Externí odkaz:
http://arxiv.org/abs/2409.20203
Autor:
Abramovich, Talor, Udeshi, Meet, Shao, Minghao, Lieret, Kilian, Xi, Haoran, Milner, Kimberly, Jancheska, Sofija, Yang, John, Jimenez, Carlos E., Khorrami, Farshad, Krishnamurthy, Prashanth, Dolan-Gavitt, Brendan, Shafique, Muhammad, Narasimhan, Karthik, Karri, Ramesh, Press, Ofir
Although language model (LM) agents are demonstrating growing potential in many domains, their success in cybersecurity has been limited due to simplistic design and the lack of fundamental features for this domain. We present EnIGMA, an LM agent for
Externí odkaz:
http://arxiv.org/abs/2409.16165
Stochastic resetting, the procedure of stopping and re-initializing random processes, has recently emerged as a powerful tool for accelerating processes ranging from queuing systems to molecular simulations. However, its usefulness is severely limite
Externí odkaz:
http://arxiv.org/abs/2409.14419
Crafting a single, versatile physics-based controller that can breathe life into interactive characters across a wide spectrum of scenarios represents an exciting frontier in character animation. An ideal controller should support diverse control mod
Externí odkaz:
http://arxiv.org/abs/2409.14393
Autor:
Church, Jonathan R., Blumer, Ofir, Keidar, Tommer D., Ploutno, Leo, Reuveni, Shlomi, Hirshberg, Barak
We present a procedure for enhanced sampling of molecular dynamics simulations through informed stochastic resetting. Many phenomena, such as protein folding and crystal nucleation, occur over time scales that are inaccessible using standard simulati
Externí odkaz:
http://arxiv.org/abs/2409.10115
Stochastic resetting, a method for accelerating target search in random processes, often incurs temporal and energetic costs. For a diffusing particle, a lower bound exists for the energetic cost of reaching the target, which is attained at low reset
Externí odkaz:
http://arxiv.org/abs/2409.10108
Autor:
Gildenblat, Jacob, Hadar, Ofir
We introduce Segmentation by Factorization (F-SEG), an unsupervised segmentation method for pathology that generates segmentation masks from pre-trained deep learning models. F-SEG allows the use of pre-trained deep neural networks, including recentl
Externí odkaz:
http://arxiv.org/abs/2409.05697