Zobrazeno 1 - 10
of 24 824
pro vyhledávání: '"SRIDHAR, P"'
Autor:
Mathai, Alex, Sedamaki, Kranthi, Das, Debeshee, Mathews, Noble Saji, Tamilselvam, Srikanth, Chimalakonda, Sridhar, Kumar, Atul
Machine Learning (ML) for software engineering (SE) has gained prominence due to its ability to significantly enhance the performance of various SE applications. This progress is largely attributed to the development of generalizable source code repr
Externí odkaz:
http://arxiv.org/abs/2411.14611
Routability optimization in modern EDA tools has benefited greatly from using machine learning (ML) models. Constructing and optimizing the performance of ML models continues to be a challenge. Neural Architecture Search (NAS) serves as a tool to aid
Externí odkaz:
http://arxiv.org/abs/2411.14296
Autor:
Sridhar, Arjun, Chen, Yiran
Neural Architecture Search (NAS) continues to serve a key roll in the design and development of neural networks for task specific deployment. Modern NAS techniques struggle to deal with ever increasing search space complexity and compute cost constra
Externí odkaz:
http://arxiv.org/abs/2411.14498
Autor:
Shen, Yichen, Hsieh, Ping-Yen, Sridhar, Sashank Kaushik, Feldman, Samantha, Chang, You-Chia, Smith, Thomas A., Dutt, Avik
Squeezed light, with its quantum noise reduction capabilities, has emerged as a powerful resource in quantum information processing and precision metrology. To reach noise reduction levels such that a quantum advantage is achieved, off-chip squeezers
Externí odkaz:
http://arxiv.org/abs/2411.11679
Autor:
Sridhar, Aditya
Music genre classification is a critical component of music recommendation systems, generation algorithms, and cultural analytics. In this work, we present an innovative model for classifying music genres using attention-based temporal signature mode
Externí odkaz:
http://arxiv.org/abs/2411.14474
Modern industrial infrastructures rely heavily on Cyber-Physical Systems (CPS), but these are vulnerable to cyber-attacks with potentially catastrophic effects. To reduce these risks, anomaly detection methods based on physical invariants have been d
Externí odkaz:
http://arxiv.org/abs/2411.10918
By means of two-dimensional general relativistic resistive magnetohydrodynamic simulations, we investigate the properties of the sheath separating the black hole jet from the surrounding medium. We find that the electromagnetic power flowing through
Externí odkaz:
http://arxiv.org/abs/2411.10662
Autor:
Gupta, Ravi Kant, Jindal, Mohit, Jain, Garima, Sridhar, Epari, Yadav, Subhash, Jain, Hasmukh, Shet, Tanuja, Sakhdeo, Uma, Sengar, Manju, Nayak, Lingaraj, Bagal, Bhausaheb, Apkare, Umesh, Sethi, Amit
We address the challenge of automated classification of diffuse large B-cell lymphoma (DLBCL) into its two primary subtypes: activated B-cell-like (ABC) and germinal center B-cell-like (GCB). Accurate classification between these subtypes is essentia
Externí odkaz:
http://arxiv.org/abs/2411.08531
Autor:
Srinivasan, Dhruv, Beyer, Alex, Zhu, Daiwei, Churchill, Spencer, Mehta, Kushagra, Sridhar, Sashank Kaushik, Chakrabarti, Kushal, Steuerman, David W., Chopra, Nikhil, Dutt, Avik
The Fermi-Hubbard model (FHM) is a simple yet rich model of strongly interacting electrons with complex dynamics and a variety of emerging quantum phases. These properties make it a compelling target for digital quantum simulation. Trotterization-bas
Externí odkaz:
http://arxiv.org/abs/2411.07778
Autor:
Naik, Hemal, Yang, Junran, Das, Dipin, Crofoot, Margaret C, Rathore, Akanksha, Sridhar, Vivek Hari
Understanding animal behaviour is central to predicting, understanding, and mitigating impacts of natural and anthropogenic changes on animal populations and ecosystems. However, the challenges of acquiring and processing long-term, ecologically rele
Externí odkaz:
http://arxiv.org/abs/2411.06896