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MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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Journal Papers
29
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Journal Papers
29
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Alternate Geometric and Semantic Denoising Diffusion for Protein Inverse Folding
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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2026-01-01
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Wang, Chenglin; Zhou, Yucheng; Wang, Zhe; Zhai, Zijie; Shen, Jianbing; Zhang, Kai
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Self-generated Cross-Modal Prompt Tuning
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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2026-01-01
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Cao, Guiming; Wu, Zonghan; Huo, Huan; Ou, Yuming; Xu, Guandong
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Efficient Approximate Temporal Triangle Counting in Streaming with Predictions
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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2026-01-01
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Venturing, Giorgio; Sarpe, Ilie; Vandin, Fabio
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Memory-Enhanced Invariant Prompt Learning for Urban Flow Prediction Under Distribution Shifts
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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2026-01-01
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Jiang, Haiyang; Chen, Tong; Zhang, Wentao; Quoc Viet Hung Nguyen; Yuan, Yuan; Li, Yong; Yin, Hongzhi
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Uncertainty-Aware Metabolic Stability Prediction with Dual-View Contrastive Learning
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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2026-01-01
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Guo, Peijin; Lie, Minghui; Pan, Hewen; Chen, Bowen; Wu, Yang; Guo, Zikang; Zhang, Leo Yu; Hu, Shengshan; Hu, Shengqing
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Towards Deeper GCNs: Alleviating Over-Smoothing via Iterative Training and Fine-Tuning
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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2026-01-01
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Peng, Furong; Gao, Jinzhen; Lu, Xuan; Liu, Kang; Huo, Yifan; Wang, Sheng
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Stable Vision Concept Transformers for Medical Diagnosis
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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2026-01-01
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Hu, Lijie; Lai, Songning; Hua, Yuan; Yang, Shu; Zhang, Jingfeng; Wang, Di
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Quality-Preserving Extreme Image Compression: Using Interpretable Conditioning Inputs with Diffusion Models
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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2026-01-01
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Hassan, Shayan Ali; Humair, Danish; Qazi, Ihsan Ayyub; Qazi, Zafar Ayyub
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Community-Aware Graph Transformer: Preserving Community Semantics for Effective Global Aggregation
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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2026-01-01
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Duan, Yutai; Liu, Jie; Wu, Jianhua; Liu, Jialin
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GraphWeave : Interpretable and Robust Graph Generation via Random Walk Trajectories
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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2026-01-01
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Nandakumar, Rahul; Chakrabarti, Deepayan
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MPG: An Efficient Multi-scale Point-Based GNN for Non-uniform Meshes
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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2026-01-01
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Wu, Qinxin; Liu, Pengwei; Ren, Xingyu; Ni, Dong
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DINGHY: Null Models for Non-degenerate Directed Hypergraphs
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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2026-01-01
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Abuissa, Maryam; Riondato, Matteo; Upfal, Eli
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EDN: A Novel Edge-Dependent Noise Model for Graph Data
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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2026-01-01
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Kumar, Pintu; Hemachandran, Nandyala
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The Densest SWAMP Problem: Subhypergraphs with Arbitrary Monotonic Partial Edge Rewards
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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2026-01-01
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Bengali, Vedangi; Tatti, Nikolaj; Kumpulainen, Iiro; Adriaens, Florian; Veldt, Nate
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AB-STE: Adaptive Blended Gradient Estimation for Efficient Binarized Networks
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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2026-01-01
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Gupta, Siddharth; Kumar, Akash
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Conformalized Exceptional Model Mining: Telling Where Your Model Performs (Not) Well
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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2026-01-01
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Du, Xin; Yang, Sikun; Duivesteijn, Wouter; Pechenizkiy, Mykola
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How Useful Is Graph Pooling for Node-Level Tasks?
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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2026-01-01
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Duan, Yijun; Liu, Xin; Lynden, Steven; Matono, Akiyoshi; Ma, Qiang
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Interpretable Hybrid-Rule Temporal Point Processes
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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2026-01-01
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Cao, Yunyang; Lin, Juekai; Wang, Hongye; Li, Wenhao; Jin, Bo
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Towards Better Generalization and Interpretability in Unsupervised Concept-Based Models
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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2026-01-01
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De Santis, Francesco; Bich, Philippe; Ciravegna, Gabriele; Barbiero, Pietro; Cerquitelli, Tania; Giordano, Danilo
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Backdoor Attacks on Graph Classification via Data Augmentation and Dynamic Poisoning
MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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2026-01-01
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Wang, Yadong; Zhang, Zhiwei; Qiao, Pengpeng; Yuan, Ye; Wang, Guoren
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