Zobrazeno 1 - 10
of 31 229
pro vyhledávání: '"Hafez, A"'
Humanoids have the potential to be the ideal embodiment in environments designed for humans. Thanks to the structural similarity to the human body, they benefit from rich sources of demonstration data, e.g., collected via teleoperation, motion captur
Externí odkaz:
http://arxiv.org/abs/2411.01349
Autor:
Hafez-Torbati, Mohsen
The antiferromagnetic quantum Hall insulator (AFQHI) where one of the spin components is in the quantum Hall state and the other in the trivial state is an established phase emerging as a result of the Hubbard repulsion in spinful quantum Hall system
Externí odkaz:
http://arxiv.org/abs/2410.23367
Autor:
Hafez, Ahmad
Recently, there has been a substantial amount of interest in GNN-based anomaly detection. Existing efforts have focused on simultaneously mastering the node representations and the classifier necessary for identifying abnormalities with relatively sh
Externí odkaz:
http://arxiv.org/abs/2409.15304
Inspired by the success of the Transformer architecture in natural language processing and computer vision, we investigate the use of Transformers in Reinforcement Learning (RL), specifically in modeling the environment's dynamics using Transformer D
Externí odkaz:
http://arxiv.org/abs/2407.18841
Learning a locomotion controller for a musculoskeletal system is challenging due to over-actuation and high-dimensional action space. While many reinforcement learning methods attempt to address this issue, they often struggle to learn human-like gai
Externí odkaz:
http://arxiv.org/abs/2407.11658
Autor:
Hafez-Torbati, Mohsen
Publikováno v:
Phys. Rev. B 110, 115147 (2024)
The cooperation of electronic correlation and spin-orbit coupling can stabilize magnetic topological insulators which host novel quantum phenomena such as the quantum anomalous Hall state also known as Chern insulator (CI). Here, we investigate the e
Externí odkaz:
http://arxiv.org/abs/2407.02630
Autor:
Ghaemi, Hafez, Jamshidi, Shirin, Mashreghi, Mohammad, Ahmadabadi, Majid Nili, Kebriaei, Hamed
Markov games (MGs) and multi-agent reinforcement learning (MARL) are studied to model decision making in multi-agent systems. Traditionally, the objective in MG and MARL has been risk-neutral, i.e., agents are assumed to optimize a performance metric
Externí odkaz:
http://arxiv.org/abs/2406.06041
Autor:
Nanwani, Laksh, Gupta, Kumaraditya, Mathur, Aditya, Agrawal, Swayam, Hafez, A. H. Abdul, Krishna, K. Madhava
Publikováno v:
Advanced Robotics - Taylor and Francis - 2024
Humans excel at forming mental maps of their surroundings, equipping them to understand object relationships and navigate based on language queries. Our previous work SI Maps [1] showed that having instance-level information and the semantic understa
Externí odkaz:
http://arxiv.org/abs/2404.17922
In this paper, we propose reachability analysis using constrained polynomial logical zonotopes. We perform reachability analysis to compute the set of states that could be reached. To do this, we utilize a recently introduced set representation calle
Externí odkaz:
http://arxiv.org/abs/2403.18564
Autor:
Talukder, Md. Simul Hasan, Akter, Sharmin, Nur, Abdullah Hafez, Aljaidi, Mohammad, Sulaiman, Rejwan Bin, Alkoradees, Ali Fayez
Sugarcane, a key crop for the world's sugar industry, is prone to several diseases that have a substantial negative influence on both its yield and quality. To effectively manage and implement preventative initiatives, diseases must be detected promp
Externí odkaz:
http://arxiv.org/abs/2403.18870