Hematological disorders require accurate and timely diagnosis for effective treatment and patient management. This research develops a new framework that uses deep learning to rapidly identify blood disorders from per...
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The introduction of drone technology has transformed a variety of businesses, from surveillance and monitoring to delivery services. However, effective communication among drones is critical for guaranteeing smooth op...
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Decarbonization of transportation is determined to be achieved by designing and deploying cutting-edge electric vehicles (EVs) with low costs and long-distance driving ranges, as well as ensuring their reliability and...
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This paper introduces AbotalebNet, a novel deep learning architecture optimized for time series forecasting, with a particular focus on the complexities of COVID-19 data. AbotalebNet's architecture is mathematical...
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Generative Flow Networks (GFlowNets) have been shown effective to generate combinatorial objects with desired properties. We here propose a new GFlowNet training framework, with policy-dependent rewards, that bridges ...
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Generative Flow Networks (GFlowNets) have been shown effective to generate combinatorial objects with desired properties. We here propose a new GFlowNet training framework, with policy-dependent rewards, that bridges keeping flow balance of GFlowNets to optimizing the expected accumulated reward in traditional Reinforcement-Learning (RL). This enables the derivation of new policy-based GFlowNet training methods, in contrast to existing ones resembling value-based RL. It is known that the design of backward policies in GFlowNet training affects efficiency. We further develop a coupled training strategy that jointly solves GFlowNet forward policy training and backward policy design. Performance analysis is provided with a theoretical guarantee of our policy-based GFlowNet training. Experiments on both simulated and real-world datasets verify that our policy-based strategies provide advanced RL perspectives for robust gradient estimation to improve GFlowNet performance. Our code is available at: ***/niupuhua1234/GFN-PG. Copyright 2024 by the author(s)
Accurate segmentation of brain tumors in MRI images is crucial for diagnosis, treatment planning, and disease monitoring. Traditional manual segmentation methods are time- consuming and prone to variability, while sta...
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Health is one of the most precious aspects of every person's life. Whether we're talking about a well-functioning heart, nervous system, respiratory system, or simply body weight, each of these branches contri...
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For determining the appropriate treatment for brain tumors, an accurate diagnosis is necessary. Many studies have focused on the deep learning-based classification of brain tumors. This study employed a comprehensive ...
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Motifs are functional elements in DNA, RNA, and protein sequences. Motif finding in molecular sequences is well studied. However, applying machine learning techniques specifically integrating cytoplasmic/nuclear relat...
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Heart disease is one of the most common diseases in Jordan. It is a major reason of death among Jordanian adult citizens. Worldwide, an average of 56,000 people dies each day or one death every 1.5 seconds. Hence, thi...
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