{"total":15,"rows":[{"id":"2410.02698","title":"Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups","created":"2024-10-03","cited_by_count":24,"area":null},{"id":"2305.02251","title":"Automated Scientific Discovery: From Equation Discovery to Autonomous Discovery Systems","created":"2023-05-03","cited_by_count":19,"area":null},{"id":"2308.10436","title":"Approximately Equivariant Graph Networks","created":"2023-08-21","cited_by_count":16,"area":null},{"id":"2209.14991","title":"Machine learning and invariant theory","created":"2022-09-29","cited_by_count":13,"area":null},{"id":"2301.13724","title":"Towards fully covariant machine learning","created":"2023-01-31","cited_by_count":10,"area":null},{"id":"2306.06327","title":"Any-dimensional equivariant neural networks","created":"2023-06-10","cited_by_count":9,"area":null},{"id":"2312.16160","title":"SymmPI: Predictive Inference for Data with Group Symmetries","created":"2023-12-26","cited_by_count":8,"area":null},{"id":"2303.04217","title":"AI for Science: An Emerging Agenda","created":"2023-03-07","cited_by_count":5,"area":null},{"id":"2308.01362","title":"Explainable Deep Learning for Tumor Dynamic Modeling and Overall Survival Prediction using Neural-ODE","created":"2023-08-02","cited_by_count":5,"area":null},{"id":"2405.18095","title":"Is machine learning good or bad for the natural sciences?","created":"2024-05-28","cited_by_count":4,"area":null},{"id":"2406.01552","title":"Tensor learning with orthogonal, Lorentz, and symplectic symmetries","created":"2024-06-03","cited_by_count":3,"area":null},{"id":"2310.19039","title":"Machine Learning for the identification of phase-transitions in interacting agent-based systems: a Desai-Zwanzig example","created":"2023-10-29","cited_by_count":0,"area":null},{"id":"2609.38094","title":"Dimensionally consistent surrogate modelling through dimensional analysis and harmonic expansions","created":"2026-09-29","cited_by_count":0,"area":null},{"id":"2609.38916","title":"Warm-starting PDE solvers with any-dimensional machine learning","created":"2026-09-30","cited_by_count":0,"area":null},{"id":"2610.18871","title":"Cepheid: Decoupling Scale from Structure for Cross-Family Motion Completion","created":"2026-10-13","cited_by_count":0,"area":null}],"next_cursor":null}