pdebench/PDEBench
PDEBench: An Extensive Benchmark for Scientific Machine Learning
This project provides a comprehensive benchmark for evaluating machine learning models designed to solve Partial Differential Equations (PDEs). It offers a wide range of realistic physical problems, along with ready-to-use datasets containing various initial/boundary conditions and PDE parameters. Scientists, engineers, and researchers working with scientific machine learning can use this to compare and develop methods for simulating complex physical phenomena.
1,082 stars. Actively maintained with 1 commit in the last 30 days. Available on PyPI.
Use this if you are developing or evaluating machine learning models for scientific simulations and need a diverse, challenging, and standardized set of physical problems and datasets.
Not ideal if you are looking for a standalone simulation tool or a deep learning library for general-purpose tasks outside of scientific machine learning benchmarks.
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1,082
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141
Language
Python
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Last pushed
Feb 24, 2026
Commits (30d)
1
Dependencies
11
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