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README.md

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## Paper Info
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<h4 align="center">ConFIG: Towards Conflict-free Training of Physics Informed Neural Networks</h4>
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<h6 align="center"><img src="./docs/assets/TUM.svg" width="16"> <a href="https://tum-pbs.github.io/">Qiang Liu</a>, <img src="./docs/assets/PKU.svg" width="12"> <a href="https://rachelcmy.github.io/">Mengyu Chu</a>, and <img src="./docs/assets/TUM.svg" width="16"> <a href="https://ge.in.tum.de/about/n-thuerey/">Nils Thuerey</a></h6>
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<h6 align="center"><img src="./docs/assets/TUM.svg" width="16"> <a href="https://tum-pbs.github.io/">Qiang Liu</a>, <img src="./docs/assets/PKU.svg" width="14"> <a href="https://rachelcmy.github.io/">Mengyu Chu</a>, and <img src="./docs/assets/TUM.svg" width="16"> <a href="https://ge.in.tum.de/about/n-thuerey/">Nils Thuerey</a></h6>
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<h6 align="center">
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<img src="./docs/assets/TUM.svg" width="16"> Technical University of Munich

docs/index.md

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## Paper Info
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<h4 align="center">ConFIG: Towards Conflict-free Training of Physics Informed Neural Networks</h4>
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<h6 align="center"><img src="./assets/TUM.svg" width="16"> <a href="https://tum-pbs.github.io/">Qiang Liu</a>, <img src="./assets/PKU.svg" width="12"> <a href="https://rachelcmy.github.io/">Mengyu Chu</a>, and <img src="./assets/TUM.svg" width="16"> <a href="https://ge.in.tum.de/about/n-thuerey/">Nils Thuerey</a></h6>
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<h6 align="center"><img src="./assets/TUM.svg" width="16"> <a href="https://tum-pbs.github.io/">Qiang Liu</a>, <img src="./assets/PKU.svg" width="14"> <a href="https://rachelcmy.github.io/">Mengyu Chu</a>, and <img src="./assets/TUM.svg" width="16"> <a href="https://ge.in.tum.de/about/n-thuerey/">Nils Thuerey</a></h6>
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<h6 align="center">
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<img src="./assets/TUM.svg" width="16"> Technical University of Munich

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