{"total":45,"rows":[{"id":"2102.05152","title":"On Explainability of Graph Neural Networks via Subgraph Explorations","created":"2021-02-09","cited_by_count":281,"area":null},{"id":"2102.10757","title":"Self-Supervised Learning of Graph Neural Networks: A Unified Review","created":"2021-02-22","cited_by_count":184,"area":null},{"id":"2102.01189","title":"GraphDF: A Discrete Flow Model for Molecular Graph Generation","created":"2021-02-01","cited_by_count":180,"area":null},{"id":"2102.05013","title":"Spherical Message Passing for 3D Graph Networks","created":"2021-02-09","cited_by_count":168,"area":null},{"id":"2203.15046","title":"AUC Maximization in the Era of Big Data and AI: A Survey","created":"2022-03-28","cited_by_count":100,"area":null},{"id":"2209.11807","title":"Periodic Graph Transformers for Crystal Material Property Prediction","created":"2022-09-23","cited_by_count":87,"area":null},{"id":"2102.00546","title":"GraphEBM: Molecular Graph Generation with Energy-Based Models","created":"2021-01-31","cited_by_count":85,"area":null},{"id":"2103.12608","title":"DIG: A Turnkey Library for Diving into Graph Deep Learning Research","created":"2021-03-23","cited_by_count":76,"area":null},{"id":"2206.08515","title":"ComENet: Towards Complete and Efficient Message Passing for 3D Molecular Graphs","created":"2022-06-17","cited_by_count":69,"area":null},{"id":"2207.12600","title":"Learning Hierarchical Protein Representations via Complete 3D Graph Networks","created":"2022-07-26","cited_by_count":55,"area":null},{"id":"2304.04757","title":"A new perspective on building efficient and expressive 3D equivariant graph neural networks","created":"2023-04-07","cited_by_count":47,"area":null},{"id":"2306.04922","title":"Efficient and Equivariant Graph Networks for Predicting Quantum Hamiltonian","created":"2023-06-08","cited_by_count":39,"area":null},{"id":"2306.10045","title":"Efficient Approximations of Complete Interatomic Potentials for Crystal Property Prediction","created":"2023-06-12","cited_by_count":37,"area":null},{"id":"2104.08736","title":"Stochastic Optimization of Areas Under Precision-Recall Curves with Provable Convergence","created":"2021-04-18","cited_by_count":35,"area":null},{"id":"2110.01717","title":"Molecule3D: A Benchmark for Predicting 3D Geometries from Molecular Graphs","created":"2021-09-30","cited_by_count":31,"area":null},{"id":"2203.00176","title":"When AUC meets DRO: Optimizing Partial AUC for Deep Learning with Non-Convex Convergence Guarantee","created":"2022-03-01","cited_by_count":29,"area":null},{"id":"2310.14029","title":"LLM-Prop: Predicting Physical And Electronic Properties Of Crystalline Solids From Their Text Descriptions","created":"2023-10-21","cited_by_count":29,"area":null},{"id":"2202.00529","title":"Molecular Representation Learning via Heterogeneous Motif Graph Neural Networks","created":"2022-02-01","cited_by_count":23,"area":null},{"id":"2308.15568","title":"Over-Squashing in Graph Neural Networks: A Comprehensive survey","created":"2023-08-29","cited_by_count":23,"area":null},{"id":"2202.08335","title":"Task-Agnostic Graph Explanations","created":"2022-02-16","cited_by_count":20,"area":null},{"id":"2202.13248","title":"Automated Data Augmentations for Graph Classification","created":"2022-02-26","cited_by_count":20,"area":null},{"id":"2306.03065","title":"LibAUC: A Deep Learning Library for X-Risk Optimization","created":"2023-06-05","cited_by_count":15,"area":null},{"id":"2206.00260","title":"Multi-block Min-max Bilevel Optimization with Applications in Multi-task Deep AUC Maximization","created":"2022-06-01","cited_by_count":11,"area":null},{"id":"2106.08551","title":"Fast Quantum Property Prediction via Deeper 2D and 3D Graph Networks","created":"2021-06-16","cited_by_count":10,"area":null},{"id":"2203.14177","title":"Benchmarking Deep AUROC Optimization: Loss Functions and Algorithmic Choices","created":"2022-03-27","cited_by_count":10,"area":null},{"id":"2303.03761","title":"Graph Neural Networks in Vision-Language Image Understanding: A Survey","created":"2023-03-07","cited_by_count":10,"area":null},{"id":"2211.14042","title":"Molecular Joint Representation Learning via Multi-modal Information","created":"2022-11-25","cited_by_count":8,"area":null},{"id":"2402.07249","title":"Impact of Domain Knowledge and Multi-Modality on Intelligent Molecular Property Prediction: A Systematic Survey","created":"2024-02-11","cited_by_count":6,"area":null},{"id":"2202.03341","title":"Neighbor2Seq: Deep Learning on Massive Graphs by Transforming Neighbors to Sequences","created":"2022-02-07","cited_by_count":4,"area":null},{"id":"2301.02242","title":"Graph Contrastive Learning for Multi-omics Data","created":"2023-01-03","cited_by_count":4,"area":null},{"id":"2405.18577","title":"Single-Loop Stochastic Algorithms for Difference of Max-Structured Weakly Convex Functions","created":"2024-05-28","cited_by_count":4,"area":null},{"id":"2305.08040","title":"Provable Multi-instance Deep AUC Maximization with Stochastic Pooling","created":"2023-05-14","cited_by_count":3,"area":null},{"id":"2508.00619","title":"DACTYL: Diverse Adversarial Corpus of Texts Yielded from Large Language Models","created":"2025-08-01","cited_by_count":3,"area":null},{"id":"2211.02720","title":"Deep Surrogate Docking: Accelerating Automated Drug Discovery with Graph Neural Networks","created":"2022-11-04","cited_by_count":2,"area":null},{"id":"2305.13315","title":"3D Molecular Geometry Analysis with 2D Graphs","created":"2023-05-01","cited_by_count":1,"area":null},{"id":"2312.14936","title":"PerCNet: Periodic Complete Representation for Crystal Graphs","created":"2023-12-03","cited_by_count":1,"area":null},{"id":"2401.11768","title":"ADA-GNN: Atom-Distance-Angle Graph Neural Network for Crystal Material Property Prediction","created":"2024-01-22","cited_by_count":1,"area":null},{"id":"2606.18390","title":"MOLAR: Learning Multimodal Molecular Representations from Noisy Labels","created":"2026-06-16","cited_by_count":1,"area":null},{"id":"2109.04881","title":"ProcK: Machine Learning for Knowledge-Intensive Processes","created":"2021-09-10","cited_by_count":0,"area":null},{"id":"2305.15776","title":"AUC Optimization from Multiple Unlabeled Datasets","created":"2023-05-25","cited_by_count":0,"area":null},{"id":"2402.06673","title":"Advancing Explainable AI Toward Human-Like Intelligence: Forging the Path to Artificial Brain","created":"2024-02-07","cited_by_count":0,"area":null},{"id":"2405.18724","title":"Adapting Differential Molecular Representation with Hierarchical Prompts for Multi-label Property Prediction","created":"2024-05-29","cited_by_count":0,"area":null},{"id":"2507.03430","title":"Multi-Level Fusion Graph Neural Network for Molecule Property Prediction","created":"2025-07-04","cited_by_count":0,"area":null},{"id":"2606.19374","title":"Protein Representation Learning with Secondary-Structure and Energy-Filtered Hydrogen-Bond Graphs","created":"2026-06-12","cited_by_count":0,"area":null},{"id":"2609.21151","title":"EnSol: an environment-aware graph neural network for molecular solubility prediction","created":"2026-09-17","cited_by_count":0,"area":null}],"next_cursor":null}