A flexible framework for solving PDEs with modern spectral methods.
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Updated
Jul 21, 2024 - Python
A flexible framework for solving PDEs with modern spectral methods.
High performance computational platform in Python for the spectral Galerkin method
[NeurIPS'21] Shape As Points: A Differentiable Poisson Solver
Implementation of Directional Graph Networks in PyTorch and DGL
Systems Neuroscience Computing in Python: user-friendly analysis of large-scale electrophysiology data
Comparison of various numerical methods for computational fluid dynamics
Fast and flexible two- and three-point correlation analysis for time series using spectral methods.
Radio-wave transfer matrix model for glacier ice
ManifoldEM Python suite
A Python-Based Elliptic Solver in Axisymmetry
[WWW 2023] "Addressing Heterophily in Graph Anomaly Detection: A Perspective of Graph Spectrum" by Yuan Gao, Xiang Wang, Xiangnan He, Zhenguang Liu, Huamin Feng, Yongdong Zhang
PySpectral is a Python package for solving the partial differential equation (PDE) of Burgers' equation in its deterministic and stochastic version.
Pseudospectral Kolmogorov Flow Solver
Runge-Kutta adaptive-step solvers for nonlinear PDEs. Solvers include both exponential time differencing and integrating factor methods.
Working with numerical grids made easy.
Software implementation for paper Heuristic Analysis of Manifolds from Simulated Cryo-EM Ensemble Data
📈 Common API (C++ and Python) for Fast Fourier Transform HPC libraries (publish-only mirror)
Codes to solve a scalar wave equation using spacetime discretization methods.
Fourier-Hermite Galerkin method applied to the Vlasov-Poisson equation
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