Zobrazeno 1 - 10
of 36 758
pro vyhledávání: '"Than Aung"'
Theory and observations reveal that the circumgalactic medium (CGM) and the cosmic web at high redshifts are multiphase, with small clouds of cold gas embedded in a hot, diffuse medium. A proposed mechanism is `shattering' of large, thermally unstabl
Externí odkaz:
http://arxiv.org/abs/2410.12914
Heart failure remains a major global health challenge, contributing significantly to the 17.8 million annual deaths from cardiovascular disease, highlighting the need for improved diagnostic tools. Current heart disease prediction models based on cla
Externí odkaz:
http://arxiv.org/abs/2410.07446
Autor:
Chan, Jun Shern, Chowdhury, Neil, Jaffe, Oliver, Aung, James, Sherburn, Dane, Mays, Evan, Starace, Giulio, Liu, Kevin, Maksin, Leon, Patwardhan, Tejal, Weng, Lilian, Mądry, Aleksander
We introduce MLE-bench, a benchmark for measuring how well AI agents perform at machine learning engineering. To this end, we curate 75 ML engineering-related competitions from Kaggle, creating a diverse set of challenging tasks that test real-world
Externí odkaz:
http://arxiv.org/abs/2410.07095
Autor:
Aung, Aye Phyu Phyu, Wang, Xinrun, Wang, Ruiyu, Chan, Hau, An, Bo, Li, Xiaoli, Senthilnath, J.
In this paper, we propose a new approach to train deep learning models using game theory concepts including Generative Adversarial Networks (GANs) and Adversarial Training (AT) where we deploy a double-oracle framework using best response oracles. GA
Externí odkaz:
http://arxiv.org/abs/2410.04764
Autor:
Li, Hailin, Ramachandra, Raghavendra, Ragab, Mohamed, Mondal, Soumik, Tan, Yong Kiam, Aung, Khin Mi Mi
Smartphone-based contactless fingerphoto authentication has become a reliable alternative to traditional contact-based fingerprint biometric systems owing to rapid advances in smartphone camera technology. Despite its convenience, fingerprint authent
Externí odkaz:
http://arxiv.org/abs/2409.18636
Continual learning (CL) adapt the deep learning scenarios with timely updated datasets. However, existing CL models suffer from the catastrophic forgetting issue, where new knowledge replaces past learning. In this paper, we propose Continual Learnin
Externí odkaz:
http://arxiv.org/abs/2409.17806
Autor:
Atthaphan, Ek-ong, Kaewsnod, Attaphon, Xu, Kai, Aung, Moh Moh, Sreethawong, Warintorn, Limphirat, Ayut, Yan, Yupeng
We explore the meson cloud contribution to nucleon electromagnetic form factors in dispersion relation approach. In our calculations, experimental data on transition amplitudes for pion-nucleon scatterings are taken directly as inputs, with the assum
Externí odkaz:
http://arxiv.org/abs/2409.17492
Autor:
Maw, Aung Phone
We present outlines of a general method to reach certain kinds of $q$-multiple sum identities. Throughout our exposition, we shall give generalizations to the results given by Dilcher, Prodinger, Fu and Lascoux, Zeng, and Guo and Zhang concerning $q$
Externí odkaz:
http://arxiv.org/abs/2409.16330
Molecular optimization is a key challenge in drug discovery and material science domain, involving the design of molecules with desired properties. Existing methods focus predominantly on single-property optimization, necessitating repetitive runs to
Externí odkaz:
http://arxiv.org/abs/2409.07786
The proliferation of data-intensive and low-latency applications has driven the development of multi-access edge computing (MEC) as a viable solution to meet the increasing demands for high-performance computing and storage capabilities at the networ
Externí odkaz:
http://arxiv.org/abs/2408.12860