辫子带来帮助 发表于 2025-3-26 23:56:02
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Lecture Notes in Computer Sciencehttp://image.papertrans.cn/k/image/541652.jpgInstrumental 发表于 2025-3-27 11:30:33
,Optimisation of Matrix Production System Reconfiguration with Reinforcement Learning,f an MPS. We define two operational scenarios and evaluate the potential of RL in each. Taken more generally, our results provide context to better understand when RL can be beneficial in industrial-scale use cases.捐助 发表于 2025-3-27 17:00:51
: ,emistry ,ware ,onvex ,ull ,utoencoder Towards Inverse Molecular Design,resentation for inverse design to discover novel molecules. However, exploring this latent space requires particular insights to generate new structures. Therefore, we propose using a convex hull (CH) surrounding the top molecules regarding high QEDs to ensnare a tight subspace in the latent represeendoscopy 发表于 2025-3-27 20:12:01
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,Interactive Link Prediction as a Downstream Task for Foundational GUI Understanding Models, a second screen (target screen). If this task is solved sufficiently, it can demonstrate an understanding of the relationship between elements and components across screens and enable various applications in GUI design automation and assistance. To encourage and support research on interactive link昆虫 发表于 2025-3-28 02:51:09
Harmonizing Feature Attributions Across Deep Learning Architectures: Enhancing Interpretability andoss diverse deep-learning models. Our findings highlight the potential for harmonized feature attribution methods to improve interpretability and foster trust in machine learning applications, regardless of the underlying architecture.Coronary-Spasm 发表于 2025-3-28 06:35:05
,Detecting Floors in Residential Buildings,nd existing approaches are completely black-box so that it is difficult to determine when and why the prediction is wrong..In this paper we propose a grey-box approach. In a stepwise process we can predict floor counts with high quality and remain explainable and parametrizable. By using data that i胎儿 发表于 2025-3-28 12:02:49
,A Comparative Study of Video-Based Analysis Using Machine Learning for Polyp Classification,e integration of such a voting system within the broader framework of video-based polyp identification and provides an empirical evaluation of its performance when juxtaposed with contemporary models. The findings underscore the potential of the proposed system in advancing colorectal polyp classifi