Yuesong Shen

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Daniel CremersTechnical University of MunichVerified email at tum.de
Christian TomaniTechnical University of MunichVerified email at tum.de
Hans Hao-Hsun HsuTechnische Universität MünchenVerified email at tum.de
Wang XiaoResearch assistant, Technical University of MunichVerified email at tum.de
Huilin YinTongji University Associate Professor For Control EngineeringVerified email at tongji.edu.cn
Walter StecheleTechnical University of Munich (TUM)Verified email at tum.de
Jun YanPhd. Candiate of Tongji UniversityVerified email at tongji.edu.cn
Mohammad Emtiyaz KhanCenter for Advanced Intelligence Project (AIP), RIKEN, TokyoVerified email at postman.riken.jp
Thomas MoellenhoffResearch Scientist, RIKEN AIPVerified email at postman.riken.jp
Nico DaheimTU Darmstadt, ETH Zürich, ELLISVerified email at ukp.informatik.tu-darmstadt.de
Bai CongTokyo Institute of TechnologyVerified email at m.titech.ac.jp
Claire-Hélène DemartySenior Scientist, InterDigitalVerified email at interdigital.com
Gian Maria MarconiMachine Learning Research Engineer, Woven by ToyotaVerified email at woven.toyota
Peter NicklPhD researcher, University of GenevaVerified email at unige.ch
Iryna GurevychFull Professor, TU Darmstadt; Adjunct Professor, MBZUAI, UAE; Affiliated Professor, INSAIT, BulgariaVerified email at cs.tu-darmstadt.de
Yu WangNetflixVerified email at netflix.com
Futa WasedaThe University of TokyoVerified email at g.ecc.u-tokyo.ac.jp
Marvin EisenbergerPhD Student, Technische Universität MünchenVerified email at in.tum.de
Christian KokeTechnical University of MunichVerified email at tum.de
Abhishek SarohaVerified email at in.tum.de

Yuesong Shen

Technical University of Munich

Verified email at tum.de

Deep Learning Machine Learning


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Trajectory prediction for intelligent vehicles using spatial‐attention mechanism J Yan, Z Peng, H Yin, J Wang, X Wang, Y Shen, W Stechele, D Cremers IET Intelligent Transport Systems 14 (13), 1855-1863, 2020	45	2020
What makes graph neural networks miscalibrated? HHH Hsu, Y Shen, C Tomani, D Cremers Advances in Neural Information Processing Systems 35, 13775-13786, 2022	34	2022
Deep learning for multimodal-based video interestingness prediction Y Shen, CH Demarty, NQK Duong 2017 IEEE International Conference on Multimedia and Expo (ICME), 1003-1008, 2017	11	2017
Variational learning is effective for large deep networks Y Shen, N Daheim, B Cong, P Nickl, GM Marconi, C Bazan, R Yokota, ... arXiv preprint arXiv:2402.17641, 2024	8	2024
Explicit pairwise factorized graph neural network for semi-supervised node classification Y Wang, Y Shen, D Cremers Uncertainty in Artificial Intelligence, 1979-1987, 2021	7	2021
Beyond in-domain scenarios: robust density-aware calibration C Tomani, FK Waseda, Y Shen, D Cremers International Conference on Machine Learning, 34344-34368, 2023	6	2023
A graph is more than its nodes: Towards structured uncertainty-aware learning on graphs HHH Hsu, Y Shen, D Cremers NeurIPS 2022 Workshop: New Frontiers in Graph Learning, 2022	6	2022
A chain graph interpretation of real-world neural networks Y Shen, D Cremers arXiv preprint arXiv:2006.16856, 2020	4	2020
Deep combinatorial aggregation Y Shen, D Cremers Advances in Neural Information Processing Systems 35, 32299-32310, 2022	3	2022
ResolvNet: A Graph Convolutional Network with multi-scale Consistency C Koke, A Saroha, Y Shen, M Eisenberger, D Cremers arXiv preprint arXiv:2310.00431, 2023	1	2023
Probabilistic discriminative learning with layered graphical models Y Shen, T Wu, C Domokos, D Cremers arXiv preprint arXiv:1902.00057, 2019	1	2019
Variational Low-Rank Adaptation Using IVON B Cong, N Daheim, Y Shen, D Cremers, R Yokota, ME Khan, T Möllenhoff arXiv preprint arXiv:2411.04421, 2024		2024
Transferability for Graph Convolutional Networks C Koke, A Saroha, Y Shen, M Eisenberger, MM Bronstein, D Cremers ICML 2024 Workshop on Geometry-grounded Representation Learning and …, 0

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