scimlPhysics-informed neural networks 2019-10-15 – 2022-12-09Deep sets invariant and equivariant functions 2022-11-24 – 2022-12-08Machine learning for physical sciences Turbulent mixing at the boundary between two disciplines with differing inertia and viscosity 2017-05-15 – 2022-12-07Nonparametrically learning dynamical systems 2018-08-13 – 2022-12-06Deep learning as a dynamical system 2018-08-13 – 2022-10-30Ensemble Kalman methods for training neural networks Data assimilation for network weights 2022-09-20Neural PDE operator learning 2019-10-15 – 2022-08-29Machine learning for partial differential equations 2017-05-15 – 2022-08-29Neural learning for spatiotemporal systems 2020-09-16 – 2022-07-28Differentiable PDE solvers 2017-05-15 – 2022-07-20Learning with conservation laws, invariances and symmetries 2020-04-11 – 2022-02-25Learning summary statistics 2020-04-22 – 2021-07-15Statistical mechanics of statistics 2016-12-01 – 2021-01-06
Machine learning for physical sciences Turbulent mixing at the boundary between two disciplines with differing inertia and viscosity 2017-05-15 – 2022-12-07
Ensemble Kalman methods for training neural networks Data assimilation for network weights 2022-09-20