Zobrazeno 1 - 10
of 13 070
pro vyhledávání: '"Toumi, A."'
Predicting human intent is challenging yet essential to achieving seamless Human-Robot Collaboration (HRC). Many existing approaches fail to fully exploit the inherent relationships between objects, tasks, and the human model. Current methods for pre
Externí odkaz:
http://arxiv.org/abs/2410.00302
Human intelligence possesses the ability to effectively focus on important environmental components, which enhances perception, learning, reasoning, and decision-making. Inspired by this cognitive mechanism, we introduced a novel concept termed relev
Externí odkaz:
http://arxiv.org/abs/2409.13998
Effective human-robot collaboration (HRC) requires the robots to possess human-like intelligence. Inspired by the human's cognitive ability to selectively process and filter elements in complex environments, this paper introduces a novel concept and
Externí odkaz:
http://arxiv.org/abs/2409.07753
Autor:
Yin, Zhenghao, Agresti, Iris, de Felice, Giovanni, Brown, Douglas, Toumi, Alexis, Pentangelo, Ciro, Piacentini, Simone, Crespi, Andrea, Ceccarelli, Francesco, Osellame, Roberto, Coecke, Bob, Walther, Philip
Recently, machine learning had a remarkable impact, from scientific to everyday-life applications. However, complex tasks often imply unfeasible energy and computational power consumption. Quantum computation might lower such requirements, although i
Externí odkaz:
http://arxiv.org/abs/2407.20364
Examining the community structures within intricate networks is crucial for comprehending their intrinsic dynamics and functionality. The paper presents the Fast Local Move Iterated Greedy (FLMIG) algorithm, a novel method designed to effectively ide
Externí odkaz:
http://arxiv.org/abs/2406.14751
We introduce an Invertible Symbolic Regression (ISR) method. It is a machine learning technique that generates analytical relationships between inputs and outputs of a given dataset via invertible maps (or architectures). The proposed ISR method natu
Externí odkaz:
http://arxiv.org/abs/2405.06848
This paper investigates the social optimum for a dynamic linear quadratic collective choice problem where a group of agents choose among multiple alternatives or destinations. The agents' common objective is to minimize the average cost of the entire
Externí odkaz:
http://arxiv.org/abs/2403.10612
In this work, we present an adjoint-based method for discovering the underlying governing partial differential equations (PDEs) given data. The idea is to consider a parameterized PDE in a general form and formulate a PDE-constrained optimization pro
Externí odkaz:
http://arxiv.org/abs/2401.17177
Perception serves as a critical component in the functionality of autonomous agents. However, the intricate relationship between perception metrics and robotic metrics remains unclear, leading to ambiguity in the development and fine-tuning of percep
Externí odkaz:
http://arxiv.org/abs/2312.07744
DisCoPy is a Python toolkit for computing with monoidal categories. It comes with two flexible data structures for string diagrams: the first one for planar monoidal categories based on lists of layers, the second one for symmetric monoidal categorie
Externí odkaz:
http://arxiv.org/abs/2311.10608