{"total":26,"rows":[{"id":"2405.15429","title":"E(n) Equivariant Topological Neural Networks","created":"2024-05-24","cited_by_count":22,"area":null},{"id":"2410.11443","title":"Are High-Degree Representations Really Unnecessary in Equivariant Graph Neural Networks?","created":"2024-10-15","cited_by_count":18,"area":null},{"id":"2502.16533","title":"A Survey of Graph Transformers: Architectures, Theories and Applications","created":"2025-02-23","cited_by_count":14,"area":null},{"id":"2411.09429","title":"AI-driven inverse design of materials: Past, present and future","created":"2024-11-14","cited_by_count":10,"area":null},{"id":"2505.16379","title":"Materials Generation in the Era of Artificial Intelligence: A Comprehensive Survey","created":"2025-05-22","cited_by_count":10,"area":null},{"id":"2407.06053","title":"Learning local equivariant representations for quantum operators","created":"2024-07-08","cited_by_count":8,"area":null},{"id":"2407.02025","title":"On the Expressive Power of Sparse Geometric MPNNs","created":"2024-07-02","cited_by_count":7,"area":null},{"id":"2506.19482","title":"Fast and Distributed Equivariant Graph Neural Networks by Virtual Node Learning","created":"2025-06-24","cited_by_count":6,"area":null},{"id":"2409.19838","title":"Using pretrained graph neural networks with token mixers as geometric featurizers for conformational dynamics","created":"2024-09-30","cited_by_count":5,"area":null},{"id":"2506.19862","title":"DualEquiNet: A Dual-Space Hierarchical Equivariant Network for Large Biomolecules","created":"2025-06-10","cited_by_count":5,"area":null},{"id":"2410.09795","title":"WGFormer: An SE(3)-Transformer Driven by Wasserstein Gradient Flows for Molecular Ground-State Conformation Prediction","created":"2024-10-13","cited_by_count":4,"area":null},{"id":"2505.09203","title":"InvDesFlow-AL: active learning-based workflow for inverse design of functional materials","created":"2025-05-14","cited_by_count":4,"area":null},{"id":"2507.04225","title":"Zero-Shot Cyclic Peptide Design via Composable Geometric Constraints","created":"2025-07-06","cited_by_count":4,"area":null},{"id":"2501.07373","title":"Dynami-CAL GraphNet: A Physics-Informed Graph Neural Network Conserving Linear and Angular Momentum for Dynamical Systems","created":"2025-01-13","cited_by_count":3,"area":null},{"id":"2510.13169","title":"Universally Invariant Learning in Equivariant GNNs","created":"2025-10-15","cited_by_count":3,"area":null},{"id":"2410.11323","title":"KA-GNN: Kolmogorov-Arnold Graph Neural Networks for Molecular Property Prediction","created":"2024-10-15","cited_by_count":2,"area":null},{"id":"2509.03885","title":"Topotein: Topological Deep Learning for Protein Representation Learning","created":"2025-09-04","cited_by_count":2,"area":null},{"id":"2510.04233","title":"PAINET: A Principled Efficient Transformer for 3D Dynamics Modeling","created":"2025-10-05","cited_by_count":2,"area":null},{"id":"2510.15403","title":"Geometric Mixture Models for Electrolyte Conductivity Prediction","created":"2025-10-17","cited_by_count":2,"area":null},{"id":"2601.04104","title":"Equivariant Neural Networks for Force-Field Models of Lattice Systems","created":"2026-01-07","cited_by_count":2,"area":null},{"id":"2503.02209","title":"CrystalFramer: Rethinking the Role of Frames for SE(3)-Invariant Crystal Structure Modeling","created":"2025-03-04","cited_by_count":0,"area":null},{"id":"2508.19884","title":"Parameter-Free Structural-Diversity Message Passing for Graph Neural Networks","created":"2025-08-27","cited_by_count":0,"area":null},{"id":"2510.16023","title":"A Conformation-Centric Generative Foundation Model for Linear Polymer Modeling and Design","created":"2025-10-15","cited_by_count":0,"area":null},{"id":"2602.20176","title":"Cross-Chirality Generalization by Axial Vectors for Hetero-Chiral Protein-Peptide Interaction Design","created":"2026-02-13","cited_by_count":0,"area":null},{"id":"2607.02573","title":"Symmetry-Structured Neural Completion of Islamic Geometric Patterns from Sparse Control Geometry","created":"2026-06-30","cited_by_count":0,"area":null},{"id":"2608.12010","title":"Reducing Symmetry Increase in Equivariant Neural Networks","created":"2026-08-12","cited_by_count":0,"area":null}],"next_cursor":null}