# NeuralPDE: How to implement the MiniMax adaptive reweighting method

**URL:** <https://discourse.julialang.org/t/neuralpde-how-to-implement-the-minimax-adaptive-reweighting-method/74443>\
**Category:** New to Julia\
**Tags:** question, package\
**Created:** [January 11, 2022, 10:38pm UTC](https://discourse.julialang.org/t/neuralpde-how-to-implement-the-minimax-adaptive-reweighting-method/74443 "2022-01-11T22:38:12Z")\
**Posts on this page:** 3\
**Page:** 1

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**Author:** ![hha08](https://avatars.discourse-cdn.com/v4/letter/h/35a633/32.png) [@hha08](https://discourse.julialang.org/u/hha08)\
**Post date:** [January 11, 2022, 10:38pm UTC](https://discourse.julialang.org/t/neuralpde-how-to-implement-the-minimax-adaptive-reweighting-method/74443/1 "2022-01-11T22:38:12Z")

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I am a newbie to Julia but have a big passion for learning it. Recently, I have been interested in solving PDE using NeuralPDE.jl after reading the paper at [https://arxiv.org/ftp/arxiv/papers/2107/2107.09443.pdf](https://arxiv.org/ftp/arxiv/papers/2107/2107.09443.pdf). Then, I want to implement the minimax adaptive reweighting method using NeuralPDE.jl to solve a linear complementarity problem. Is there anyone who knows how to do it?

Thanks.

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**Author:** ![ChrisRackauckas](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/chrisrackauckas/32/77_2.png) [@ChrisRackauckas](https://discourse.julialang.org/u/ChrisRackauckas)\
**Post date:** [January 11, 2022, 10:40pm UTC](https://discourse.julialang.org/t/neuralpde-how-to-implement-the-minimax-adaptive-reweighting-method/74443/2 "2022-01-11T22:40:49Z")

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@zobot needs to finish [https://github.com/SciML/NeuralPDE.jl/pull/291](https://github.com/SciML/NeuralPDE.jl/pull/291) 😅

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**Author:** ![hha08](https://avatars.discourse-cdn.com/v4/letter/h/35a633/32.png) [@hha08](https://discourse.julialang.org/u/hha08)\
**Post date:** [January 11, 2022, 10:45pm UTC](https://discourse.julialang.org/t/neuralpde-how-to-implement-the-minimax-adaptive-reweighting-method/74443/3 "2022-01-11T22:45:45Z")

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Thanks, Chris! I am very impressed with NeuralPDE.jl. I look forward to seeing improvements!