Zobrazeno 1 - 10
of 21
pro vyhledávání: '"Saleh, Ehsan"'
This work proposes a solution for the problem of training physics-informed networks under partial integro-differential equations. These equations require an infinite or a large number of neural evaluations to construct a single residual for training.
Externí odkaz:
http://arxiv.org/abs/2305.17387
Autor:
Ghaffari, Saba, Saleh, Ehsan, Schwing, Alexander G., Wang, Yu-Xiong, Burke, Martin D., Sinha, Saurabh
Protein design, a grand challenge of the day, involves optimization on a fitness landscape, and leading methods adopt a model-based approach where a model is trained on a training set (protein sequences and fitness) and proposes candidates to explore
Externí odkaz:
http://arxiv.org/abs/2305.13650
In this paper, we present a policy gradient method that avoids exploratory noise injection and performs policy search over the deterministic landscape. By avoiding noise injection all sources of estimation variance can be eliminated in systems with d
Externí odkaz:
http://arxiv.org/abs/2205.15379
Learning accurate classifiers for novel categories from very few examples, known as few-shot image classification, is a challenging task in statistical machine learning and computer vision. The performance in few-shot classification suffers from the
Externí odkaz:
http://arxiv.org/abs/2110.02529
Akademický článek
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Autor:
Ghaffari, Saba, Saleh, Ehsan, Schwing, Alexander G., Wang, Yu-Xiong, Burke, Martin D., Sinha, Saurabh
The problem of designing protein sequences with desired properties is challenging, as it requires to explore a high-dimensional protein sequence space with extremely sparse meaningful regions. This has led to the development of model-based optimizati
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::8fc900b69a6b69e2b72f90c27986019d
http://arxiv.org/abs/2305.13650
http://arxiv.org/abs/2305.13650
Autor:
Hades, Suha Ahmad, Saleh, Ehsan Fadhel
Publikováno v:
IOP Conference Series: Earth & Environmental Science; Sep2023, Vol. 1262 Issue 1, p1-8, 8p
Autor:
Hades, Suha Ahmad, Saleh, Ehsan Fadhel
Publikováno v:
Journal of Kirkuk University for Agricultural Sciences; 2023, Vol. 14 Issue 3, p130-140, 11p
Akademický článek
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Publikováno v:
Evolving Systems; Apr2023, Vol. 14 Issue 2, p191-206, 16p