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ORCIDPKDD / ECML 2025: Porto, Portugal - Part III
- Rita P. Ribeiro
, Bernhard Pfahringer, Nathalie Japkowicz, Pedro Larrañaga, Alípio M. Jorge, Carlos Soares, Pedro H. Abreu, João Gama:
Machine Learning and Knowledge Discovery in Databases. Research Track - European Conference, ECML PKDD 2025, Porto, Portugal, September 15-19, 2025, Proceedings, Part III. Lecture Notes in Computer Science 16015, Springer 2026, ISBN 978-3-032-06065-5
Graph Neural Networks
- Qinxin Wu, Pengwei Liu, Xingyu Ren, Dong Ni:
MPG: An Efficient Multi-scale Point-Based GNN for Non-uniform Meshes. 3-18 - Haokai Zhang, Shengtao Zhang, Zijian Cai, Heng Wang, Ruixuan Zhu, Zinan Zeng, Minnan Luo:
Unveiling the Hidden: Movie Genre and User Bias in Spoiler Detection. 19-36 - Yaya Zhao, Kaiqi Zhao, Zixuan Tang, Xiaoling Lu, Yuanyuan Zhang, Yalei Du:
GraphJCL: A Dual-Perspective Graph-Based Framework for Urban Region Representation via Joint Contrastive Learning. 37-53
Graphs and Networks
- Maryam Abuissa, Matteo Riondato, Eli Upfal:
DiNgHy: Null Models for Non-degenerate Directed Hypergraphs. 57-74 - Vedangi Bengali, Nikolaj Tatti, Iiro Kumpulainen, Florian Adriaens, Nate Veldt:
The Densest SWAMP Problem: Subhypergraphs with Arbitrary Monotonic Partial Edge Rewards. 75-91 - Yijun Duan, Xin Liu, Steven J. Lynden, Akiyoshi Matono, Qiang Ma:
How Useful Is Graph Pooling for Node-Level Tasks? 92-107 - Yutai Duan, Jie Liu, Jianhua Wu, Jialin Liu:
Community-Aware Graph Transformer: Preserving Community Semantics for Effective Global Aggregation. 108-124 - Siddharth Gupta, Akash Kumar:
AB-STE: Adaptive Blended Gradient Estimation for Efficient Binarized Networks. 125-140 - Haiyang Jiang, Tong Chen, Wentao Zhang, Quoc Viet Hung Nguyen, Yuan Yuan, Yong Li, Hongzhi Yin:
Memory-Enhanced Invariant Prompt Learning for Urban Flow Prediction Under Distribution Shifts. 141-159 - Pintu Kumar, Nandyala Hemachandra:
EDN: A Novel Edge-Dependent Noise Model for Graph Data. 160-176 - Zhuoran Li, Yucen Gao, Yu Yin, Xinle Li, Hui Gao, Xiaofeng Gao, Guihai Chen:
DRNCS: Dual-Level Route Generation Model Based on Node Contraction and Shortcuts. 177-192 - Rahul Nandakumar, Deepayan Chakrabarti:
GraphWeave : Interpretable and Robust Graph Generation via Random Walk Trajectories. 193-210 - Furong Peng, Jinzhen Gao, Xuan Lu, Kang Liu, Yifan Huo, Sheng Wang:
Towards Deeper GCNs: Alleviating Over-Smoothing via Iterative Training and Fine-Tuning. 211-227 - Boshen Shi, Yongqing Wang, Fangda Guo, Jiangli Shao, Huawei Shen, Xueqi Cheng:
BotTrans: A Multi-source Graph Domain Adaptation Approach for Social Bot Detection. 228-243 - Giorgio Venturin, Ilie Sarpe, Fabio Vandin:
Efficient Approximate Temporal Triangle Counting in Streaming with Predictions. 244-262 - Yadong Wang, Zhiwei Zhang, Pengpeng Qiao, Ye Yuan, Guoren Wang:
Backdoor Attacks on Graph Classification via Data Augmentation and Dynamic Poisoning. 263-279
Healthcare and Bioinformatics
- Arthur Buzelin, Pedro Dutenhefner, Turi Rezende, Luisa G. Porfírio, Pedro Bento, Yan Aquino, Jose Fernandes, Caio Santana, Gabriela Miana, Gisele L. Pappa, Antônio L. P. Ribeiro, Wagner Meira Jr.:
A CNN-Based Local-Global Self-attention via Averaged Window Embeddings for Hierarchical ECG Analysis. 283-299 - Peijin Guo, Minghui Li, Hewen Pan, Bowen Chen, Yang Wu, Zikang Guo, Leo Yu Zhang, Shengshan Hu, Shengqing Hu:
Uncertainty-Aware Metabolic Stability Prediction with Dual-View Contrastive Learning. 300-316 - Lijie Hu, Songning Lai, Yuan Hua, Shu Yang, Jingfeng Zhang, Di Wang:
Stable Vision Concept Transformers for Medical Diagnosis. 317-332 - Chen Li, Yoshihiro Yamanishi:
Gx2Mol: De Novo Generation of Hit-Like Molecules from Gene Expression Profiles. 333-349 - Chenglin Wang, Yucheng Zhou, Zhe Wang, Zijie Zhai, Jianbing Shen, Kai Zhang:
Alternate Geometric and Semantic Denoising Diffusion for Protein Inverse Folding. 350-366
Images and Computer Vision
- Guiming Cao, Zonghan Wu, Huan Huo, Yuming Ou, Guandong Xu:
Self-generated Cross-Modal Prompt Tuning. 369-386 - Shayan Ali Hassan, Danish Humair, Ihsan Ayyub Qazi, Zafar Ayyub Qazi:
Quality-Preserving Extreme Image Compression: Using Interpretable Conditioning Inputs with Diffusion Models. 387-404 - Kaiwei Sun, Luhan Wang, Jin Wang:
Beyond General Edge Utilization: Edge Attention Mean Teacher for Semi-Supervised Medical Image Segmentation. 405-421
Interpretability and Explainability
- Sieben Bocklandt, Vincent Derkinderen, Koen Vanderstraeten, Wouter Pijpops, Kurt Jaspers, Luc De Raedt, Wannes Meert:
Queryable and Interpretable PU Learning Through Probabilistic Circuits. 425-442 - Yunyang Cao, Juekai Lin, Hongye Wang, Wenhao Li, Bo Jin:
Interpretable Hybrid-Rule Temporal Point Processes. 443-459 - Jasper De Laet, Hamed Behzadi-Khormouji, Lucas Deckers, José Oramas:
SVEBI: Towards the Interpretation and Explanation of Spiking Neural Networks. 460-477 - Francesco De Santis, Philippe Bich, Gabriele Ciravegna, Pietro Barbiero, Tania Cerquitelli, Danilo Giordano:
Towards Better Generalization and Interpretability in Unsupervised Concept-Based Models. 478-494 - Caglar Demir, Moshood Yekini, Michael Röder, Yasir Mahmood, Axel-Cyrille Ngonga Ngomo:
Tree-Based OWL Class Expression Learner over Large Graphs. 495-511 - Fabian Denoodt, Bart de Boer, José Oramas:
Smooth InfoMax - Towards Easier Post-Hoc Interpretability. 512-527 - Xin Du, Sikun Yang, Wouter Duivesteijn, Mykola Pechenizkiy:
Conformalized Exceptional Model Mining: Telling Where Your Model Performs (Not) Well. 528-544
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