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MACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III

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论文数29
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期刊论文 29
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Alternate Geometric and Semantic Denoising Diffusion for Protein Inverse Folding交替几何和语义去噪扩散用于蛋白质逆向折叠
deleteMACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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deleteWang, Chenglin; Zhou, Yucheng; Wang, Zhe; Zhai, Zijie; Shen, Jianbing; Zhang, Kai
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Self-generated Cross-Modal Prompt Tuning自生成跨模态提示微调
deleteMACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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deleteCao, Guiming; Wu, Zonghan; Huo, Huan; Ou, Yuming; Xu, Guandong
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Efficient Approximate Temporal Triangle Counting in Streaming with Predictions流式数据中基于预测的高效近似时间三角形计数
deleteMACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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deleteVenturing, Giorgio; Sarpe, Ilie; Vandin, Fabio
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Memory-Enhanced Invariant Prompt Learning for Urban Flow Prediction Under Distribution Shifts分布偏移下用于城市流预测的记忆增强不变提示学习
deleteMACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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deleteJiang, 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基于双视图对比学习的面向不确定性的代谢稳定性预测
deleteMACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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deleteGuo, 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迈向更深层次的图卷积网络：通过迭代训练和微调缓解过平滑问题
deleteMACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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deletePeng, Furong; Gao, Jinzhen; Lu, Xuan; Liu, Kang; Huo, Yifan; Wang, Sheng
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Stable Vision Concept Transformers for Medical Diagnosis稳定视觉概念转换器用于医学诊断
deleteMACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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deleteHu, 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保真度保持的极端图像压缩：使用可解释的条件输入与扩散模型
deleteMACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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deleteHassan, 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社区感知图Transformer：保留社区语义以实现有效的全局聚合
deleteMACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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deleteDuan, Yutai; Liu, Jie; Wu, Jianhua; Liu, Jialin
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GraphWeave : Interpretable and Robust Graph Generation via Random Walk TrajectoriesGraphWeave：基于随机游走轨迹的可解释且鲁棒图生成
deleteMACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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deleteNandakumar, Rahul; Chakrabarti, Deepayan
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MPG: An Efficient Multi-scale Point-Based GNN for Non-uniform MeshesMPG：一种用于非均匀网格的高效多尺度基于点的图神经网络
deleteMACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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deleteWu, Qinxin; Liu, Pengwei; Ren, Xingyu; Ni, Dong
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DINGHY: Null Models for Non-degenerate Directed HypergraphsDINGHY: 非退化有向超图的空模型
deleteMACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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deleteAbuissa, Maryam; Riondato, Matteo; Upfal, Eli
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EDN: A Novel Edge-Dependent Noise Model for Graph Data
deleteMACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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deleteKumar, Pintu; Hemachandran, Nandyala
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The Densest SWAMP Problem: Subhypergraphs with Arbitrary Monotonic Partial Edge Rewards最密集的SWAMP问题：具有任意单调部分边收益的子超图
deleteMACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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deleteBengali, Vedangi; Tatti, Nikolaj; Kumpulainen, Iiro; Adriaens, Florian; Veldt, Nate
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AB-STE: Adaptive Blended Gradient Estimation for Efficient Binarized NetworksAB-STE：用于高效二值化网络的适应性混合梯度估计
deleteMACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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deleteGupta, Siddharth; Kumar, Akash
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Conformalized Exceptional Model Mining: Telling Where Your Model Performs (Not) Well归一化异常模型挖掘：告诉你的模型在何处表现良好（或表现不佳）
deleteMACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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deleteDu, Xin; Yang, Sikun; Duivesteijn, Wouter; Pechenizkiy, Mykola
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How Useful Is Graph Pooling for Node-Level Tasks?图池化对于节点级任务有多有用？
deleteMACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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deleteDuan, Yijun; Liu, Xin; Lynden, Steven; Matono, Akiyoshi; Ma, Qiang
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Interpretable Hybrid-Rule Temporal Point Processes可解释的混合规则时间点过程
deleteMACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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deleteCao, Yunyang; Lin, Juekai; Wang, Hongye; Li, Wenhao; Jin, Bo
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Towards Better Generalization and Interpretability in Unsupervised Concept-Based Models面向无监督概念模型的更好泛化性和可解释性
deleteMACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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deleteDe 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通过数据增强和动态投毒对图分类的后门攻击
deleteMACHINE LEARNING AND KNOWLEDGE DISCOVERY IN DATABASES. RESEARCH TRACK, ECML PKDD 2025, PT III
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deleteWang, Yadong; Zhang, Zhiwei; Qiao, Pengpeng; Yuan, Ye; Wang, Guoren
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