用深度学习中的算子学习方法高效模拟泪膜破裂这一复杂物理过程，为生物流体力学提供了新工具。
arXiv:2601.08001v2 Announce Type: replace-cross Abstract: Tear film (TF) breakup is a key driver of understanding dry eye disease, yet estimating TF t…
将机器学习与偏微分方程结合，用算子学习破解周期域上的三次非线性薛定谔方程，开启科学计算新范式。
arXiv:2606.27459v1 Announce Type: new Abstract: We consider the cubic nonlinear Schr\"odinger (NLS) equation on two-dimensional flat tori with varying…
量子计算与深度学习交叉前沿：共形预测赋予量子算子网络可靠的不确定性估计，实现可扩展的无分布可信学习。
arXiv:2605.00330v2 Announce Type: replace Abstract: Operator learning enables fast surrogate modeling of high-dimensional dynamical systems, but exist…
大模型上下文学习新范式：CoO（Chain of Operators）让模型像执行程序一样连续调用算子，提升复杂任务推理能力。
arXiv:2606.12318v1 Announce Type: cross Abstract: Neural operators approximate mappings between function spaces, but often generalize poorly to other …
探索算子学习中零样本超分辨率的可行性，挑战传统认知的研究。
arXiv:2606.00296v1 Announce Type: cross Abstract: Neural operators are often reported to exhibit zero-shot super-resolution, a phenomenon in which a m…
突破性Transformer模型ArGEnT，高效学习复杂几何系统的解算子，助力设计优化、控制与反问题。
arXiv:2602.11626v2 Announce Type: replace-cross Abstract: Learning solution operators for systems with complex, varying geometries and parametric phys…