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pro vyhledávání: '"Phyu, The"'
To understand the impact of vaccination, we consider a SIVR (susceptible-infected-vaccinated-recovered) model which combines impulsive vaccination into the classical SIR model. The final size is firstly defined and estimated, and then the peak value
Externí odkaz:
http://arxiv.org/abs/2410.20456
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
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
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
Continual learning (CL) models are designed to learn new tasks arriving sequentially without re-training the network. However, real-world ML applications have very limited label information and these models suffer from catastrophic forgetting. To add
Externí odkaz:
http://arxiv.org/abs/2405.14623
This paper deals with an impulsive degenerate logistic model, where pulses are introduced for modeling interventions or disturbances, and degenerate logistic term may describe refugees or protections zones for the species. Firstly, the principal eige
Externí odkaz:
http://arxiv.org/abs/2402.12156
Autor:
Senthilnath, J., Zhou, Bangjian, Ng, Zhen Wei, Aggarwal, Deeksha, Dutta, Rajdeep, Yoon, Ji Wei, Aung, Aye Phyu Phyu, Wu, Keyu, Wu, Min, Li, Xiaoli
In the realm of sequential decision-making tasks, the exploration capability of a reinforcement learning (RL) agent is paramount for achieving high rewards through interactions with the environment. To enhance this crucial ability, we propose SAQN, a
Externí odkaz:
http://arxiv.org/abs/2402.11604
Network slicing is essential for transforming future telecommunication networks into versatile service platforms, but it also presents challenges for sustainable network operations. While meeting the requirements of network slices incurs additional e
Externí odkaz:
http://arxiv.org/abs/2312.17179
Autor:
Phyu M. Latt, Nyi N. Soe, Alicia J. King, David Lee, Tiffany R. Phillips, Xianglong Xu, Eric P. F. Chow, Christopher K. Fairley, Lei Zhang, Jason J. Ong
Publikováno v:
BMC Public Health, Vol 24, Iss 1, Pp 1-11 (2024)
Abstract Introduction Early detection and treatment of HIV and sexually transmitted infections (STIs) are crucial for effective control. We previously developed MySTIRisk, an artificial intelligence-based risk tool that predicts the risk of HIV and S
Externí odkaz:
https://doaj.org/article/059af60051104d72913da702caf194ca
Autor:
Supakorn Sripaew, Kameelah Yasharad, Dzerlina S. Rahari, Weiyan Feng, Zhenzhu Qian, Huynh Ngoc Thanh, Pei Li, Agus Fitriangga, Satiti Palupi Purwanto, Aye Nyein Phyu, Fangming Xianyu, Sombat Phadungvitvatthana, Wit Wichaidit, Ponlagrit Kumwichar, Virasakdi Chongsuvivatwong
Publikováno v:
Tropical Medicine and Health, Vol 52, Iss 1, Pp 1-12 (2024)
Abstract Background The current survey describes the seroprevalence, history of coronavirus disease 2019 (COVID-19), and vaccination status among predominantly aboriginal residents on a tourist island in southern Thailand. This information can be tra
Externí odkaz:
https://doaj.org/article/a26f49a5d8d341679a0c8758a0a975ba