Zobrazeno 1 - 10
of 6 836
pro vyhledávání: '"Malviya, A."'
Autor:
Malviya, Ashwini, Mittal, Sparsh
In this work, we compare the performance of deep learning models for classifying the spinodal dataset. We evaluate state-of-the-art models (MobileViT, NAT, EfficientNet, CNN), alongside several ensemble models (majority voting, AdaBoost). Additionall
Externí odkaz:
http://arxiv.org/abs/2410.09756
The optimal model for a given task is often challenging to determine, requiring training multiple models from scratch which becomes prohibitive as dataset and model sizes grow. A more efficient alternative is to reuse smaller pre-trained models by ex
Externí odkaz:
http://arxiv.org/abs/2405.15895
Autor:
Das, Arindam, Paul, Sudarshan, Scholz, Niko, Malviya, Akhilesh Kumar, Sistu, Ganesh, Bhattacharya, Ujjwal, Eising, Ciarán
Accurate obstacle identification represents a fundamental challenge within the scope of near-field perception for autonomous driving. Conventionally, fisheye cameras are frequently employed for comprehensive surround-view perception, including rear-v
Externí odkaz:
http://arxiv.org/abs/2402.00637
Autor:
Malviya-Thakur, Addi, Milewicz, Reed, Paganini, Lavinia, Mahmoud, Ahmed Samir Imam, Mockus, Audris
The proliferation of open-source scientific software for science and research presents opportunities and challenges. In this paper, we introduce the SciCat dataset -- a comprehensive collection of Free-Libre Open Source Software (FLOSS) projects, des
Externí odkaz:
http://arxiv.org/abs/2312.06382
Autor:
McInnes, Lois Curfman, Heroux, Michael, Bernholdt, David E., Dubey, Anshu, Gonsiorowski, Elsa, Gupta, Rinku, Marques, Osni, Moulton, J. David, Nam, Hai Ah, Norris, Boyana, Raybourn, Elaine M., Willenbring, Jim, Almgren, Ann, Bartlett, Ross, Cranfill, Kita, Fickas, Stephen, Frederick, Don, Godoy, William, Grubel, Patricia, Hartman-Baker, Rebecca, Huebl, Axel, Lynch, Rose, Thakur, Addi Malviya, Milewicz, Reed, Miller, Mark C., Mundt, Miranda, Palmer, Erik, Parete-Koon, Suzanne, Phinney, Megan, Riley, Katherine, Rogers, David M., Sims, Ben, Stevens, Deborah, Watson, Gregory R.
Computational and data-enabled science and engineering are revolutionizing advances throughout science and society, at all scales of computing. For example, teams in the U.S. DOE Exascale Computing Project have been tackling new frontiers in modeling
Externí odkaz:
http://arxiv.org/abs/2311.02010
Publikováno v:
Journal of Family Medicine and Primary Care, Vol 13, Iss 11, Pp 5370-5373 (2024)
We report an interesting case of Bancroftian filariasis diagnosed on fine needle aspiration cytology in a young female hailing from a non-endemic hilly area of India, who presented with a subcutaneous swelling on the left forearm. This is an unusual
Externí odkaz:
https://doaj.org/article/ddd27c87fc794602ab174f0fc80c8da6
Publikováno v:
Journal of Asian Ceramic Societies, Vol 12, Iss 4, Pp 306-321 (2024)
A statistically designed property database of six commercial glass families is leveraged to develop models relating viscosity to temperature and composition. Specialized models for each glass family were designed based on the Adam–Gibbs equation. W
Externí odkaz:
https://doaj.org/article/aeaf48ba38024365b8f7908703add253
Autor:
Watson, Gregory R., Malviya-Thakur, Addi, Katz, Daniel S., Raybourn, Elaine M., Hoffman, Bill, Robinson, Dana, Kellerman, John, Roundy, Clark
Research software plays a crucial role in advancing scientific knowledge, but ensuring its sustainability, maintainability, and long-term viability is an ongoing challenge. The Sustainable Research Software Institute (SRSI) Model has been designed to
Externí odkaz:
http://arxiv.org/abs/2308.14954
Autor:
Watson, Gregory R., Malviya-Thakur, Addi, Katz, Daniel S., Raybourn, Elaine M., Hoffman, Bill, Robinson, Dana, Kellerman, John, Roundy, Clark
Research software plays a crucial role in advancing scientific knowledge, but ensuring its sustainability, maintainability, and long-term viability is an ongoing challenge. To address these concerns, the Sustainable Research Software Institute (SRSI)
Externí odkaz:
http://arxiv.org/abs/2308.14953
Sharpness-aware minimization (SAM) methods have gained increasing popularity by formulating the problem of minimizing both loss value and loss sharpness as a minimax objective. In this work, we increase the efficiency of the maximization and minimiza
Externí odkaz:
http://arxiv.org/abs/2307.16704