Zobrazeno 1 - 10
of 5 313
pro vyhledávání: '"Udayan AT"'
Reservoir computing (RC), is a class of computational methods such as Echo State Networks (ESN) and Liquid State Machines (LSM) describe a generic method to perform pattern recognition and temporal analysis with any non-linear system. This is enabled
Externí odkaz:
http://arxiv.org/abs/2411.11414
Heracles: A HfO$\mathrm{_2}$ Ferroelectric Capacitor Compact Model for Efficient Circuit Simulations
Autor:
Fehlings, Luca, Ali, Md Hanif, Gibertini, Paolo, Gallicchio, Egidio A., Ganguly, Udayan, Deshpande, Veeresh, Covi, Erika
This paper presents a physics-based compact model for circuit simulations in a SPICE environment for HfO2-based ferroelectric capacitors (FeCaps). The model has been calibrated based on experimental data obtained from HfO2-based FeCaps. A thermal mod
Externí odkaz:
http://arxiv.org/abs/2410.07791
Autor:
Carvalho, Bernardo, Darji, Udayan
We discuss whether classical examples of dynamical systems satisfying the shadowing property also satisfy the shadowing property for the induced map on the hyperspace of continua, obtaining both positive and negative results. We prove that transitive
Externí odkaz:
http://arxiv.org/abs/2408.12688
We introduce a class of linear bounded invertible operators on Banach spaces, called shift operators, which comprises weighted backward shifts and models finite products of weighted backward shifts and dissipative composition operators. We classify v
Externí odkaz:
http://arxiv.org/abs/2407.20890
Autor:
Mandal, Udayan, Amir, Guy, Wu, Haoze, Daukantas, Ieva, Newell, Fletcher Lee, Ravaioli, Umberto, Meng, Baoluo, Durling, Michael, Hobbs, Kerianne, Ganai, Milan, Shim, Tobey, Katz, Guy, Barrett, Clark
In recent years, deep reinforcement learning (DRL) approaches have generated highly successful controllers for a myriad of complex domains. However, the opaque nature of these models limits their applicability in aerospace systems and safety-critical
Externí odkaz:
http://arxiv.org/abs/2407.07088
Autor:
Zhu, Qian, Wang, Dakuo, Ma, Shuai, Wang, April Yi, Chen, Zixin, Khurana, Udayan, Ma, Xiaojuan
As AI technology continues to advance, the importance of human-AI collaboration becomes increasingly evident, with numerous studies exploring its potential in various fields. One vital field is data science, including feature engineering (FE), where
Externí odkaz:
http://arxiv.org/abs/2405.14107
Autor:
Mandal, Udayan, Amir, Guy, Wu, Haoze, Daukantas, Ieva, Newell, Fletcher Lee, Ravaioli, Umberto J., Meng, Baoluo, Durling, Michael, Ganai, Milan, Shim, Tobey, Katz, Guy, Barrett, Clark
Deep reinforcement learning (DRL) is a powerful machine learning paradigm for generating agents that control autonomous systems. However, the ``black box'' nature of DRL agents limits their deployment in real-world safety-critical applications. A pro
Externí odkaz:
http://arxiv.org/abs/2405.14058
In this paper we present the results of an evaluation study of the perfor-mance of LLMs on Technical Language Processing tasks. Humans are often confronted with tasks in which they have to gather information from dispar-ate sources and require making
Externí odkaz:
http://arxiv.org/abs/2403.15503
Autor:
Bernardes Jr., Nilson C., Caraballo, Blas M., Darji, Udayan B., Fávaro, Vinícius V., Peris, Alfred
Publikováno v:
J. Funct. Anal. 288 (2025), no. 2, Paper No. 110696, 51 pp
We introduce and study the notions of (generalized) hyperbolicity, topological stability and (uniform) topological expansivity for operators on locally convex spaces. We prove that every generalized hyperbolic operator on a locally convex space has t
Externí odkaz:
http://arxiv.org/abs/2403.02843
This paper introduces a novel compact mixed integer linear programming (MILP) formulation and a discretization discovery-based solution approach for the Vehicle Routing Problem with Time Windows (VRPTW). We aim to solve the optimization problem effic
Externí odkaz:
http://arxiv.org/abs/2403.00262