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pro vyhledávání: '"Xu, YanYan"'
Human mobility studies how people move to access their needed resources and plays a significant role in urban planning and location-based services. As a paramount task of human mobility modeling, next location prediction is challenging because of the
Externí odkaz:
http://arxiv.org/abs/2412.19092
Autor:
Zhou, Chen, Cheng, Peng, Fang, Junfeng, Zhang, Yifan, Yan, Yibo, Jia, Xiaojun, Xu, Yanyan, Wang, Kun, Cao, Xiaochun
Multispectral object detection, utilizing RGB and TIR (thermal infrared) modalities, is widely recognized as a challenging task. It requires not only the effective extraction of features from both modalities and robust fusion strategies, but also the
Externí odkaz:
http://arxiv.org/abs/2411.18288
Organic synthesis stands as a cornerstone of the chemical industry. The development of robust machine learning models to support tasks associated with organic reactions is of significant interest. However, current methods rely on hand-crafted feature
Externí odkaz:
http://arxiv.org/abs/2411.17629
Autor:
Zhang, Yu, Yu, Ruijie, Zeng, Kaipeng, Li, Ding, Zhu, Feng, Yang, Xiaokang, Jin, Yaohui, Xu, Yanyan
High-throughput reaction condition (RC) screening is fundamental to chemical synthesis. However, current RC screening suffers from laborious and costly trial-and-error workflows. Traditional computer-aided synthesis planning (CASP) tools fail to find
Externí odkaz:
http://arxiv.org/abs/2407.15141
The next Point of Interest (POI) recommendation aims to recommend the next POI for users at a specific time. As users' check-in records can be viewed as a long sequence, methods based on Recurrent Neural Networks (RNNs) have recently shown good appli
Externí odkaz:
http://arxiv.org/abs/2404.00367
Autor:
Zeng, Kaipeng, yang, Bo, Zhao, Xin, Zhang, Yu, Nie, Fan, Yang, Xiaokang, Jin, Yaohui, Xu, Yanyan
Motivation: Retrosynthesis planning poses a formidable challenge in the organic chemical industry. Single-step retrosynthesis prediction, a crucial step in the planning process, has witnessed a surge in interest in recent years due to advancements in
Externí odkaz:
http://arxiv.org/abs/2404.00044
Facility location problems on graphs are ubiquitous in real world and hold significant importance, yet their resolution is often impeded by NP-hardness. Recently, machine learning methods have been proposed to tackle such classical problems, but they
Externí odkaz:
http://arxiv.org/abs/2312.15658
Publikováno v:
EPJ Data Sci., vol. 10, no. 1, p. 12, Dec. 2021
Properly extracting patterns of individual mobility with high resolution data sources such as the one extracted from smartphone applications offers important opportunities. Potential opportunities not offered by call detailed records (CDRs), which of
Externí odkaz:
http://arxiv.org/abs/2312.13505
Large language models (LLMs) face challenges in solving complex mathematical problems that require comprehensive capacities to parse the statements, associate domain knowledge, perform compound logical reasoning, and integrate the intermediate ration
Externí odkaz:
http://arxiv.org/abs/2312.08926
Publikováno v:
[J]. Travel Behaviour and Society, 2023, 33: 100606
In the era of big data, the ubiquity of location-aware portable devices provides an unprecedented opportunity to understand inhabitants' behavior and their interactions with the built environments. Among the widely used data resources, mobile phone d
Externí odkaz:
http://arxiv.org/abs/2306.03441