Zobrazeno 1 - 10
of 1 731
pro vyhledávání: '"Sakhuja, P"'
This paper presents a tool for automatically exploring the design space of deep learning accelerators (DLAs). Our main advancement is Starlight, a data-driven performance model that uses transfer learning to bridge the gap between fast, low-fidelity
Externí odkaz:
http://arxiv.org/abs/2412.15548
Autor:
Sahoo, Srilagna, Varghese, Abin, Sadashiva, Aniket, Goyal, Mayank, Sakhuja, Jayatika, Bhowmik, Debanjan, Lodha, Saurabh
Neuromorphic in-memory computing requires area-efficient architecture for seamless and low latency parallel processing of large volumes of data. Here, we report a compact, vertically integrated/stratified field-effect transistor (VSFET) consisting of
Externí odkaz:
http://arxiv.org/abs/2412.10757
Autor:
Ghaffarzadeh-Esfahani, Mohammadreza, Ghaffarzadeh-Esfahani, Mahdi, Salahi-Niri, Arian, Toreyhi, Hossein, Atf, Zahra, Mohsenzadeh-Kermani, Amirali, Sarikhani, Mahshad, Tajabadi, Zohreh, Shojaeian, Fatemeh, Bagheri, Mohammad Hassan, Feyzi, Aydin, Tarighatpayma, Mohammadamin, Gazmeh, Narges, Heydari, Fateme, Afshar, Hossein, Allahgholipour, Amirreza, Alimardani, Farid, Salehi, Ameneh, Asadimanesh, Naghmeh, Khalafi, Mohammad Amin, Shabanipour, Hadis, Moradi, Ali, Zadeh, Sajjad Hossein, Yazdani, Omid, Esbati, Romina, Maleki, Moozhan, Nasr, Danial Samiei, Soheili, Amirali, Majlesi, Hossein, Shahsavan, Saba, Soheilipour, Alireza, Goudarzi, Nooshin, Taherifard, Erfan, Hatamabadi, Hamidreza, Samaan, Jamil S, Savage, Thomas, Sakhuja, Ankit, Soroush, Ali, Nadkarni, Girish, Darazam, Ilad Alavi, Pourhoseingholi, Mohamad Amin, Safavi-Naini, Seyed Amir Ahmad
Background: This study aimed to evaluate and compare the performance of classical machine learning models (CMLs) and large language models (LLMs) in predicting mortality associated with COVID-19 by utilizing a high-dimensional tabular dataset. Materi
Externí odkaz:
http://arxiv.org/abs/2409.02136
Autor:
Sakhuja, Saiyam, Balakrishnan, S.
In a world where elections touch every aspect of society, the need for secure voting is paramount. Traditional safeguards, based on classical cryptography, rely on complex math problems like factoring large numbers. However, quantum computing is chan
Externí odkaz:
http://arxiv.org/abs/2406.19730
Autor:
Vaid, Akhil, Lampert, Joshua, Lee, Juhee, Sawant, Ashwin, Apakama, Donald, Sakhuja, Ankit, Soroush, Ali, Bick, Sarah, Abbott, Ethan, Gomez, Hernando, Hadley, Michael, Lee, Denise, Landi, Isotta, Duong, Son Q, Bussola, Nicole, Nabeel, Ismail, Muehlstedt, Silke, Freeman, Robert, Kovatch, Patricia, Carr, Brendan, Wang, Fei, Glicksberg, Benjamin, Argulian, Edgar, Lerakis, Stamatios, Khera, Rohan, Reich, David L., Kraft, Monica, Charney, Alexander, Nadkarni, Girish
Generative Large Language Models (LLMs) hold significant promise in healthcare, demonstrating capabilities such as passing medical licensing exams and providing clinical knowledge. However, their current use as information retrieval tools is limited
Externí odkaz:
http://arxiv.org/abs/2401.02851
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-10 (2024)
Abstract Reinforcement Learning (RL) is a machine learning paradigm that enhances clinical decision-making for healthcare professionals by addressing uncertainties and optimizing sequential treatment strategies. RL leverages patient-data to create pe
Externí odkaz:
https://doaj.org/article/61ef8bcd0d45499a8c53082c4b0b4079
Autor:
Eyal Klang, Donald Apakama, Ethan E. Abbott, Akhil Vaid, Joshua Lampert, Ankit Sakhuja, Robert Freeman, Alexander W. Charney, David Reich, Monica Kraft, Girish N. Nadkarni, Benjamin S. Glicksberg
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-12 (2024)
Abstract Large language models (LLMs) can optimize clinical workflows; however, the economic and computational challenges of their utilization at the health system scale are underexplored. We evaluated how concatenating queries with multiple clinical
Externí odkaz:
https://doaj.org/article/5e75fc54840d40b7b0bdf4bc508e4cab
Autor:
Patil, Shubham, Sakhuja, Jayatika, Singh, Ajay Kumar, Biswas, Anmol, Saraswat, Vivek, Kumar, Sandeep, Lashkare, Sandip, Ganguly, Udayan
Energy-efficient real-time synapses and neurons are essential to enable large-scale neuromorphic computing. In this paper, we propose and demonstrate the Schottky-Barrier MOSFET-based ultra-low power voltage-controlled current source to enable real-t
Externí odkaz:
http://arxiv.org/abs/2304.08504
Autor:
Faris Gulamali, Pushkala Jayaraman, Ashwin S. Sawant, Jacob Desman, Benjamin Fox, Annette Chang, Brian Y. Soong, Naveen Arivazagan, Alexandra S. Reynolds, Son Q. Duong, Akhil Vaid, Patricia Kovatch, Robert Freeman, Ira S. Hofer, Ankit Sakhuja, Neha S. Dangayach, David S. Reich, Alexander W. Charney, Girish N. Nadkarni
Publikováno v:
npj Digital Medicine, Vol 7, Iss 1, Pp 1-7 (2024)
Abstract Increased intracranial pressure (ICP) ≥15 mmHg is associated with adverse neurological outcomes, but needs invasive intracranial monitoring. Using the publicly available MIMIC-III Waveform Database (2000–2013) from Boston, we developed a
Externí odkaz:
https://doaj.org/article/8d9fbb73568949159dfb9737079a6077
Autor:
Vaishali Jain, Puja Sakhuja, Anil Kumar Agarwal, Ravi Sirdeshmukh, Fouzia Siraj, Poonam Gautam
Publikováno v:
Current Oncology, Vol 31, Iss 8, Pp 4455-4475 (2024)
Lymph node metastasis (LNM) is one of the major prognostic factors in human gastrointestinal carcinomas (GICs). The lymph node-positive patients have poorer survival than node-negative patients. LNM is directly associated with the recurrence and poor
Externí odkaz:
https://doaj.org/article/cd682332e5bf4c19b7248b5ffb83e4bf