Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Chinese Academy of SciencesCN2.9k papers
- Centre National de la Recherche ScientifiqueFR2.7k papers
- Istituto Nazionale di Fisica Nucleare, Laboratori Nazionali di FrascatiIT2.6k papers
- Institute of High Energy PhysicsCN2.6k papers
- University of Science and Technology of ChinaCN2.5k papers
- Peking UniversityCN2.4k papers
- University of Chinese Academy of SciencesCN2.3k papers
- Istituto Nazionale di Fisica Nucleare, Sezione di Roma IIT2.3k papers
- Institut National de Physique Nucléaire et de Physique des ParticulesFR2.3k papers
- Rutherford Appleton LaboratoryGB2.2k papers
- Istituto Nazionale di Fisica Nucleare, Sezione di GenovaIT2.2k papers
- European Organization for Nuclear ResearchCH2.2k papers
12 papers · 2 filters
Graph Learning with Spectral Connectivity Priors for Scarce Data
Mingxiao Liu, Bahar Oveisgharan, Bingyan Zou +3
Learning a sparse graph from scarce data is practically important but challenging. Motivated by the desirable combination of local sparsity and strong global connectivity exhibited…
Beyond Independent Manipulation: Individual Fairness-aware Strategic Classification with Peer Imitation
Xinpeng Lv, Chunyuan Zheng, Yunxin Mao +9
Strategic classification (SC) investigates scenarios where agents manipulate their features to obtain favorable decisions from predictive models. Existing fairness-aware SC approac…
Bridge the Gaps: Heterogeneous Attributed Graph Clustering via Quaternion Representation Learning
Xinxi Chen, Junyang Chen, Yiqun Zhang +2
Attributed graph clustering partitions nodes by jointly exploiting node attributes and graph topology. It remains challenging due to attribute heterogeneity and representation degr…
When Hard Negatives Hurt: Bridging the Generative-Discriminative Gap in Hard Negative Synthesis for Retrieval
Zhicheng Zhang, Jiwei Tang, Kuicai Dong +9
Hard negative mining has become the dominant strategy for training retrievers, yet it faces intrinsic limitations: negatives are bounded by corpus availability, selected by retriev…
Towards Accurate Model Selection in Deep Unsupervised Domain Adaptation
Kaichao You, Ximei Wang, Mingsheng Long +1
Deep unsupervised domain adaptation (Deep UDA) methods successfully leverage rich labeled data in a source domain to boost the performance on related but unlabeled data in a target…
Learning Laplacian Eigenspace with Mass-Aware Neural Operators on Point Clouds
Zherui Yang, Tao Du, Ligang Liu
The eigendecomposition of the Laplace--Beltrami Operator (LBO) is fundamental to geometric analysis, yet computing its low-frequency eigenmodes remains a significant bottleneck due…
Atoms of Thought: Universal EEG Representation Learning with Microstates
Xinyang Tian, Ruitao Liu, Ziyi Ye +3
Learning universal representations from electroencephalogram (EEG) signals is a cutting-edge approach in the field of neuroinformatics and brain-computer interfaces (BCIs). Convent…
FedGMI: Generative Model-Driven Federated Learning for Probabilistic Mixture Inference
Qijun Hou, Yuchen Shi, Pingyi Fan +1
Federated Learning (FL) facilitates collaborative model training across decentralized clients while preserving data privacy by avoiding raw data exchange. Despite its potential, FL…
RaDAR: Relation-aware Diffusion-Asymmetric Graph Contrastive Learning for Recommendation
Yixuan Huang, Jiawei Chen, Shengfan Zhang +1
Collaborative filtering (CF) recommendation has been significantly advanced by integrating Graph Neural Networks (GNNs) and Graph Contrastive Learning (GCL). However, (i) random ed…
FuseDiff: Symmetry-Preserving Joint Diffusion for Dual-Target Structure-Based Drug Design
Jianliang Wu, Anjie Qiao, Zhen Wang +2
Dual-target structure-based drug design aims to generate a single ligand together with two pocket-specific binding poses, each compatible with a corresponding target pocket, enabli…
Uncertainty-Aware Data-Based Method for Fast and Reliable Shape Optimization
Yunjia Yang, Runze Li, Yufei Zhang +1
Data-based optimization (DBO) offers a promising approach for efficiently optimizing shape for better aerodynamic performance by leveraging a pretrained surrogate model for offline…
One-Shot Price Forecasting with Covariate-Guided Experts under Privacy Constraints
Ren He, Yinliang Xu, Jinfeng Wang +2
Forecasting in power systems often involves multivariate time series with complex dependencies and strict privacy constraints across regions. Traditional forecasting methods requir…