Zobrazeno 1 - 10
of 4 227
pro vyhledávání: '"Kumar, Arun P."'
In this article, we employ physics-informed residual learning (PIRL) and propose a pricing method for European options under a regime-switching framework, where closed-form solutions are not available. We demonstrate that the proposed approach serves
Externí odkaz:
http://arxiv.org/abs/2410.10474
Autor:
Singh, Paridhi, Kumar, Arun
This paper introduces an innovative approach to open world recognition (OWR), where we leverage knowledge acquired from known objects to address the recognition of previously unseen objects. The traditional method of object modeling relies on supervi
Externí odkaz:
http://arxiv.org/abs/2406.15565
Autor:
Kumar, Arun, Schrater, Paul
People aptly exhibit general intelligence behaviors in solving a variety of tasks with flexibility and ability to adapt to novel situations by reusing and applying high-level knowledge acquired over time. But artificial agents are more like specialis
Externí odkaz:
http://arxiv.org/abs/2402.05346
Autor:
Nagrecha, Kabir, Kumar, Arun
In this paper, we propose Saturn, a new data system to improve the efficiency of multi-large-model training (e.g., during model selection/hyperparameter optimization). We first identify three key interconnected systems challenges for users building l
Externí odkaz:
http://arxiv.org/abs/2311.02840
Autor:
Pattanayak, Namrata, Kumar, Arun, Nigam, A. K, Pomjakushin, Vladimir, Nair, Sunil, Bajpai, Ashna
We consistently observe a unique pattern in remanence in a number of canted-antiferromagnets (AFM) and piezomagnets. A part of the remanence is $\textit{quasi-static}$ in nature and vanishes above a critical magnetic field. Present work is devoted to
Externí odkaz:
http://arxiv.org/abs/2310.19009
Autor:
Dhull, Monika Singh, Kumar, Arun
In this article, we discuss some geometric infinitely divisible (gid) random variables using the Laplace exponents which are Bernstein functions and study their properties. The distributional properties and limiting behavior of the probability densit
Externí odkaz:
http://arxiv.org/abs/2309.02661
Autor:
Nagrecha, Kabir, Kumar, Arun
Large language models such as GPT-3 & ChatGPT have transformed deep learning (DL), powering applications that have captured the public's imagination. These models are rapidly being adopted across domains for analytics on various modalities, often by
Externí odkaz:
http://arxiv.org/abs/2309.01226
We report a comprehensive temperature-dependent investigation of the 1:2 ordered triple perovskite system Sr$_3$CaRu$_2$O$_9$. It crystallizes in the monoclinic structure with space group $P21/c$, consisting of corner-sharing CaO$_6$ and RuO$_6$ octa
Externí odkaz:
http://arxiv.org/abs/2307.06096
Data science applications increasingly rely on heterogeneous data sources and analytics. This has led to growing interest in polystore systems, especially analytical polystores. In this work, we focus on a class of emerging multi-data model analytics
Externí odkaz:
http://arxiv.org/abs/2305.14391
Autor:
Butt Salman Pervaiz, Kakar Vivek, Kumar Arun, Razzaq Nabeel, Saleem Yasir, Ali Babar, Raposo Nuno, Ashiq Fazil, Ghori Arshad, Anderson Philip, Srivatav Nilesh, Aljabery Yazan, Abdulaziz Salman, Darr Umer, Bhatnagar Gopal
Publikováno v:
The Journal of ExtraCorporeal Technology, Vol 56, Iss 3, Pp 136-144 (2024)
Introduction: Heparin, a commonly used anticoagulant in cardiac surgery, binds to antithrombin III (ATIII) to prevent clot formation. However, heparin resistance (HR) can complicate surgical procedures, leading to increased thromboembolic risks and b
Externí odkaz:
https://doaj.org/article/527a6f8495d14906af5d949489e6b157
