Zobrazeno 1 - 10
of 164 732
pro vyhledávání: '"Prashant, A."'
Publikováno v:
Geocarto International, Vol 38, Iss 1 (2023)
Externí odkaz:
https://doaj.org/article/890140940dbf4c6cb07acdef7dc3eaa9
Autor:
Wang, Meng, Liu, Chenxu, Stein, Samuel, Ding, Yufei, Das, Poulami, Nair, Prashant J., Li, Ang
Fault-tolerant quantum computing (FTQC) is essential for executing reliable quantum computations of meaningful scale. Widely adopted QEC codes for FTQC, such as the surface code and color codes, utilize Clifford+T gate sets, where T gates are general
Externí odkaz:
http://arxiv.org/abs/2412.15434
We study the effects of hyperons, delta baryons, and quark matter phase transitions on f-mode oscillations in neutron stars. Using the density-dependent relativistic mean-field model (DDME2) for the hadronic phase and the density-dependent quark mass
Externí odkaz:
http://arxiv.org/abs/2412.12002
Autor:
Asali, Ehsan, Doshi, Prashant
We present a novel method for collaborative robots (cobots) to learn manipulation tasks and perform them in a human-like manner. Our method falls under the learn-from-observation (LfO) paradigm, where robots learn to perform tasks by observing human
Externí odkaz:
http://arxiv.org/abs/2412.11360
Autor:
Jain, Gauri, Varakantham, Pradeep, Xu, Haifeng, Taneja, Aparna, Doshi, Prashant, Tambe, Milind
Publikováno v:
PRICAI 2024: Trends in Artificial Intelligence. PRICAI 2024. Lecture Notes in Computer Science(), vol 15285
Public health practitioners often have the goal of monitoring patients and maximizing patients' time spent in "favorable" or healthy states while being constrained to using limited resources. Restless multi-armed bandits (RMAB) are an effective model
Externí odkaz:
http://arxiv.org/abs/2412.08463
Autor:
Coalson, Zachary, Woo, Jeonghyun, Chen, Shiyang, Sun, Yu, Yang, Lishan, Nair, Prashant, Fang, Bo, Hong, Sanghyun
We introduce a new class of attacks on commercial-scale (human-aligned) language models that induce jailbreaking through targeted bitwise corruptions in model parameters. Our adversary can jailbreak billion-parameter language models with fewer than 2
Externí odkaz:
http://arxiv.org/abs/2412.07192
We consider the task of out-of-distribution (OOD) generalization, where the distribution shift is due to an unobserved confounder ($Z$) affecting both the covariates ($X$) and the labels ($Y$). In this setting, traditional assumptions of covariate an
Externí odkaz:
http://arxiv.org/abs/2411.19923
Discovering causal structures with latent variables from observational data is a fundamental challenge in causal discovery. Existing methods often rely on constraint-based, iterative discrete searches, limiting their scalability to large numbers of v
Externí odkaz:
http://arxiv.org/abs/2411.19556
Point clouds acquired in constrained and challenging real-world settings are incomplete, non-uniformly sparse, or both. These obstacles present acute challenges for a vital task - point cloud completion. Using tools from Algebraic Topology and Persis
Externí odkaz:
http://arxiv.org/abs/2411.17580
Autor:
Batra, Prashant
Many upper bounds for the moduli of polynomial roots have been proposed but reportedly assessed on selected examples or restricted classes only. Regarding quality measured in terms of worst-case relative overestimation of the maximum root-modulus we
Externí odkaz:
http://arxiv.org/abs/2411.16385