Zobrazeno 1 - 10
of 31 188
pro vyhledávání: '"A Pande"'
Application profiling is an indispensable technique for many software development tasks, such as code optimization and memory management, where optimization decisions are tailored to specific program profiles. Unfortunately, modern applications codeb
Externí odkaz:
http://arxiv.org/abs/2412.06994
Autor:
Pande, Shubham, Bezugam, Sai Sukruth, Bhattacharya, Tinish, Wlazlak, Ewelina, Chakaravorty, Anjan, Chakrabarti, Bhaswar, Strukov, Dmitri
Neuromorphic systems that employ advanced synaptic learning rules, such as the three-factor learning rule, require synaptic devices of increased complexity. Herein, a novel neoHebbian artificial synapse utilizing ReRAM devices has been proposed and e
Externí odkaz:
http://arxiv.org/abs/2411.18272
Recent advancements in session-based recommendation models using deep learning techniques have demonstrated significant performance improvements. While they can enhance model sophistication and improve the relevance of recommendations, they also make
Externí odkaz:
http://arxiv.org/abs/2411.09152
We present an innovative robotic device designed to provide controlled motion for studying active matter. Motion is driven by an internal vibrator powered by a small rechargeable battery. The system integrates acoustic and magnetic sensors along with
Externí odkaz:
http://arxiv.org/abs/2411.01943
Despite the recent advancements in information retrieval (IR), zero-shot IR remains a significant challenge, especially when dealing with new domains, languages, and newly-released use cases that lack historical query traffic from existing users. For
Externí odkaz:
http://arxiv.org/abs/2410.18385
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:
Pfromm, Lukas, Kanani, Alish, Sharma, Harsh, Solanki, Parth, Tervo, Eric, Park, Jaehyun, Doppa, Janardhan Rao, Pande, Partha Pratim, Ogras, Umit Y.
Rapidly evolving artificial intelligence and machine learning applications require ever-increasing computational capabilities, while monolithic 2D design technologies approach their limits. Heterogeneous integration of smaller chiplets using a 2.5D s
Externí odkaz:
http://arxiv.org/abs/2410.09188
Autor:
Bhardwaj, Ankit, Balashankar, Ananth, Iyer, Shiva, Soans, Nita, Sudarshan, Anant, Pande, Rohini, Subramanian, Lakshminarayanan
Urban air pollution hotspots pose significant health risks, yet their detection and analysis remain limited by the sparsity of public sensor networks. This paper addresses this challenge by combining predictive modeling and mechanistic approaches to
Externí odkaz:
http://arxiv.org/abs/2410.04309
Mechanical metamaterials utilize geometry to achieve exceptional mechanical properties, including those not typically possible for traditional materials. To achieve these properties, it is necessary to identify the proper structures and geometries, w
Externí odkaz:
http://arxiv.org/abs/2410.07213
Autor:
Uzun, Baki, Pande, Shivam, Cachin-Bernard, Gwendal, Pham, Minh-Tan, Lefèvre, Sébastien, Blatrix, Rumais, McKey, Doyle
Regular patterns of vegetation are considered widespread landscapes, although their global extent has never been estimated. Among them, spotted landscapes are of particular interest in the context of climate change. Indeed, regularly spaced vegetatio
Externí odkaz:
http://arxiv.org/abs/2409.00518