{"total":25,"rows":[{"id":"2504.19496","title":"DISCO: learning to DISCover an evolution Operator for multi-physics-agnostic prediction","created":"2025-04-28","cited_by_count":21,"area":null},{"id":"2501.18972","title":"BCAT: A Block Causal Transformer for PDE Foundation Models for Fluid Dynamics","created":"2025-01-31","cited_by_count":18,"area":null},{"id":"2502.06026","title":"A Multimodal PDE Foundation Model for Prediction and Scientific Text Descriptions","created":"2025-02-09","cited_by_count":10,"area":null},{"id":"2602.00884","title":"Test-time Generalization for Physics through Neural Operator Splitting","created":"2026-01-31","cited_by_count":10,"area":null},{"id":"2510.25379","title":"A Deep Learning Framework for Multi-Operator Learning: Architectures and Approximation Theory","created":"2025-10-29","cited_by_count":9,"area":null},{"id":"2509.13805","title":"Towards a Physics Foundation Model","created":"2025-09-17","cited_by_count":8,"area":null},{"id":"2503.00300","title":"Cauchy Random Features for Operator Learning in Sobolev Space","created":"2025-03-01","cited_by_count":5,"area":null},{"id":"2601.07384","title":"CompNO: A Novel Foundation Model approach for solving Partial Differential Equations","created":"2026-01-12","cited_by_count":5,"area":null},{"id":"2605.22724","title":"Multiple Neural Operators Achieve Near-Optimal Rates for Multi-Task Learning","created":"2026-05-21","cited_by_count":4,"area":null},{"id":"2606.01470","title":"Emergent Transfer of a Physics Foundation Model from Simulation to Laboratory Turbulence","created":"2026-05-31","cited_by_count":4,"area":null},{"id":"2505.17838","title":"Continuum Transformers Perform In-Context Learning by Operator Gradient Descent","created":"2025-05-23","cited_by_count":3,"area":null},{"id":"2603.12725","title":"Graph In-Context Operator Networks for Generalizable Spatiotemporal Prediction","created":"2026-03-13","cited_by_count":3,"area":null},{"id":"2604.01961","title":"Generalization Bounds and Statistical Guarantees for Multi-Task and Multiple Operator Learning with MNO Networks","created":"2026-04-02","cited_by_count":3,"area":null},{"id":"2605.15284","title":"Tadpole: Autoencoders as Foundation Models for 3D PDEs with Online Learning","created":"2026-05-14","cited_by_count":3,"area":null},{"id":"2606.12318","title":"Chain of Operators: An Inference-Time Harness for In-Context Operator Learning","created":"2026-06-10","cited_by_count":2,"area":null},{"id":"2604.00333","title":"MVNN: A Measure-Valued Neural Network for Learning McKean-Vlasov Dynamics from Particle Data","created":"2026-04-01","cited_by_count":1,"area":null},{"id":"2604.02483","title":"A Multimodal Vision Transformer-based Modeling Framework for Prediction of Fluid Flows in Energy Systems","created":"2026-04-02","cited_by_count":1,"area":null},{"id":"2607.23337","title":"Neural operator discovery from heterogeneous trajectories","created":"2026-07-25","cited_by_count":1,"area":null},{"id":"2509.07024","title":"TGLF-WINN: Data-Efficient Deep Learning Surrogate for Turbulent Transport Modeling in Fusion","created":"2025-09-07","cited_by_count":0,"area":null},{"id":"2605.11691","title":"Compositional Neural Operators for Multi-Dimensional Fluid Dynamics","created":"2026-05-12","cited_by_count":0,"area":null},{"id":"2605.17985","title":"SAFE-SVD: Sensitivity-Aware Fidelity-Enforcing SVD for Physics Foundation Models","created":"2026-05-18","cited_by_count":0,"area":null},{"id":"2605.23712","title":"Operator Learning for Reconstructing Flow Fields from Sparse Measurements: a Language Model Approach","created":"2026-05-22","cited_by_count":0,"area":null},{"id":"2607.28432","title":"A foundation model of numerical intelligence with cross-disciplinary generalization","created":"2026-07-30","cited_by_count":0,"area":null},{"id":"2608.11831","title":"Kernel Methods for Learning Operators with Multiple Inputs and Outputs","created":"2026-08-12","cited_by_count":0,"area":null},{"id":"2609.03069","title":"Learnable composition for neural operators","created":"2026-09-02","cited_by_count":0,"area":null}],"next_cursor":null}