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Yuesong Shen
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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
502020
What makes graph neural networks miscalibrated?
HHH Hsu, Y Shen, C Tomani, D Cremers
Advances in Neural Information Processing Systems 35, 13775-13786, 2022
362022
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
212024
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
112017
Beyond in-domain scenarios: robust density-aware calibration
C Tomani, FK Waseda, Y Shen, D Cremers
International Conference on Machine Learning, 34344-34368, 2023
102023
Explicit pairwise factorized graph neural network for semi-supervised node classification
Y Wang, Y Shen, D Cremers
Uncertainty in Artificial Intelligence, 1979-1987, 2021
82021
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
62022
Deep combinatorial aggregation
Y Shen, D Cremers
Advances in Neural Information Processing Systems 35, 32299-32310, 2022
42022
A chain graph interpretation of real-world neural networks
Y Shen, D Cremers
arXiv preprint arXiv:2006.16856, 2020
42020
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
12023
Probabilistic discriminative learning with layered graphical models
Y Shen, T Wu, C Domokos, D Cremers
arXiv preprint arXiv:1902.00057, 2019
12019
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
On the successful Incorporation of Scale into Graph Neural Networks
C Koke, Y Shen, A Saroha, M Eisenberger, B Rieck, MM Bronstein, ...
ICLR 2025 Workshop on Machine Learning Multiscale Processes, 0
Graph Networks struggle with variable Scale
C Koke, Y Shen, A Saroha, M Eisenberger, B Rieck, MM Bronstein, ...
I Can't Believe It's Not Better: Challenges in Applied Deep Learning, 0
Laplace-Transform-Filters render spectral Graph Neural Networks transferable
C Koke, Y Shen, A Saroha, M Eisenberger, MM Bronstein, D Cremers
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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