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written in Julia
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DeepONets, (Fourier) Neural Operators, Physics-Informed Neural Operators, and more in Julia
A library of data interpolation and smoothing functions
Tools for building fast, hackable, pseudospectral partial differential equation solvers on periodic domains
Tools for the exploration of chaos and nonlinear dynamics
Decompose a signal/timeseries into structure and noise or seasonal and residual components
A package to represent high-order relationships between objects of any type
lecture materials of the ML for Physics course 2021 in Perimeter Institute