{"id":601,"date":"2021-01-10T19:41:41","date_gmt":"2021-01-10T23:41:41","guid":{"rendered":"http:\/\/sites.nd.edu\/jianxun-wang\/?page_id=601"},"modified":"2022-07-08T11:23:16","modified_gmt":"2022-07-08T15:23:16","slug":"software-codes","status":"publish","type":"page","link":"https:\/\/sites.nd.edu\/jianxun-wang\/software-codes\/","title":{"rendered":"Software &amp; Codes"},"content":{"rendered":"\n<div class=\"wp-block-group\"><div class=\"wp-block-group__inner-container is-layout-flow wp-block-group-is-layout-flow\">\n<p>2022, Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems [<a href=\"https:\/\/github.com\/Jianxun-Wang\/graphGalerkin\">Github Repository<\/a>]<\/p>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/sites.nd.edu\/jianxun-wang\/files\/2022\/07\/image.png\" alt=\"\" class=\"wp-image-1096\" width=\"491\" height=\"340\" srcset=\"https:\/\/sites.nd.edu\/jianxun-wang\/files\/2022\/07\/image.png 874w, https:\/\/sites.nd.edu\/jianxun-wang\/files\/2022\/07\/image-300x208.png 300w, https:\/\/sites.nd.edu\/jianxun-wang\/files\/2022\/07\/image-768x533.png 768w\" sizes=\"auto, (max-width: 491px) 100vw, 491px\" \/><\/figure>\n\n\n\n<p>2021, Physics-informed Dyna-style model-based deep reinforcement learning for dynamic control [<a href=\"https:\/\/github.com\/Jianxun-Wang\/PIMBRL\">Github Repository<\/a>]<\/p>\n\n\n\n<figure class=\"wp-block-image size-full is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/sites.nd.edu\/jianxun-wang\/files\/2022\/07\/image-1.png\" alt=\"\" class=\"wp-image-1097\" width=\"462\" height=\"260\" srcset=\"https:\/\/sites.nd.edu\/jianxun-wang\/files\/2022\/07\/image-1.png 639w, https:\/\/sites.nd.edu\/jianxun-wang\/files\/2022\/07\/image-1-300x169.png 300w\" sizes=\"auto, (max-width: 462px) 100vw, 462px\" \/><\/figure>\n<\/div><\/div>\n\n\n\n<p>2021, Super-resolution and denoising of fluid flow using physics-informed convolutional neural networks without high-resolution labels &#8212; parametric forward SR and boundary inference. [<a href=\"https:\/\/github.com\/Jianxun-Wang\/PICNNSR\" target=\"_blank\" rel=\"noreferrer noopener\">Github Repository<\/a>]<\/p>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/sites.nd.edu\/jianxun-wang\/files\/2021\/08\/Screen-Shot-2021-08-18-at-12.33.23-1024x530.png\" alt=\"\" class=\"wp-image-877\" width=\"559\" height=\"289\" srcset=\"https:\/\/sites.nd.edu\/jianxun-wang\/files\/2021\/08\/Screen-Shot-2021-08-18-at-12.33.23-1024x530.png 1024w, https:\/\/sites.nd.edu\/jianxun-wang\/files\/2021\/08\/Screen-Shot-2021-08-18-at-12.33.23-300x155.png 300w, https:\/\/sites.nd.edu\/jianxun-wang\/files\/2021\/08\/Screen-Shot-2021-08-18-at-12.33.23-768x397.png 768w, https:\/\/sites.nd.edu\/jianxun-wang\/files\/2021\/08\/Screen-Shot-2021-08-18-at-12.33.23-1536x794.png 1536w, https:\/\/sites.nd.edu\/jianxun-wang\/files\/2021\/08\/Screen-Shot-2021-08-18-at-12.33.23.png 1655w\" sizes=\"auto, (max-width: 559px) 100vw, 559px\" \/><\/figure>\n\n\n\n<p>2021, Physics-Informed Geometry-Adaptive Convolutional Neural Networks for Solving Steady-State Parametric PDEs on Irregular Domain [<a rel=\"noreferrer noopener\" href=\"https:\/\/github.com\/Jianxun-Wang\/phygeonet\" target=\"_blank\">Github Repository<\/a>]<\/p>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/sites.nd.edu\/jianxun-wang\/files\/2021\/01\/image-3.png\" alt=\"\" class=\"wp-image-604\" width=\"624\" height=\"173\" \/><\/figure>\n\n\n\n<p>2020, Physics-Constrained Bayesian Neural Network for Fluid Flow Reconstruction with Sparse and Noisy Data [<a rel=\"noreferrer noopener\" href=\"https:\/\/github.com\/Jianxun-Wang\/Physics-constrained-Bayesian-deep-learning\" target=\"_blank\">Github Repository<\/a>]<\/p>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/sites.nd.edu\/jianxun-wang\/files\/2021\/01\/image-2.png\" alt=\"\" class=\"wp-image-603\" width=\"539\" height=\"104\" srcset=\"https:\/\/sites.nd.edu\/jianxun-wang\/files\/2021\/01\/image-2.png 845w, https:\/\/sites.nd.edu\/jianxun-wang\/files\/2021\/01\/image-2-300x58.png 300w, https:\/\/sites.nd.edu\/jianxun-wang\/files\/2021\/01\/image-2-768x149.png 768w\" sizes=\"auto, (max-width: 539px) 100vw, 539px\" \/><\/figure>\n\n\n\n<p>2020, Surrogate Modeling for Fluid Flows Based on Physics-Constrained Label-Free Deep Learning  [<a rel=\"noreferrer noopener\" href=\"https:\/\/github.com\/Jianxun-Wang\/LabelFree-DNN-Surrogate\" target=\"_blank\">Github Repository<\/a>]<\/p>\n\n\n\n<figure class=\"wp-block-image size-large is-resized\"><img loading=\"lazy\" decoding=\"async\" src=\"https:\/\/sites.nd.edu\/jianxun-wang\/files\/2021\/01\/image-1.png\" alt=\"\" class=\"wp-image-602\" width=\"539\" height=\"171\" srcset=\"https:\/\/sites.nd.edu\/jianxun-wang\/files\/2021\/01\/image-1.png 851w, https:\/\/sites.nd.edu\/jianxun-wang\/files\/2021\/01\/image-1-300x95.png 300w, https:\/\/sites.nd.edu\/jianxun-wang\/files\/2021\/01\/image-1-768x243.png 768w\" sizes=\"auto, (max-width: 539px) 100vw, 539px\" \/><\/figure>\n","protected":false},"excerpt":{"rendered":"<p>2022, Physics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems [Github Repository] 2021, Physics-informed Dyna-style model-based deep reinforcement learning for dynamic control [Github Repository] 2021, Super-resolution and denoising of fluid flow using physics-informed convolutional neural networks without high-resolution labels &#8212; parametric forward SR and boundary inference. [Github Repository] 2021, [&hellip;]<\/p>\n","protected":false},"author":3220,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"footnotes":""},"class_list":["post-601","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/sites.nd.edu\/jianxun-wang\/wp-json\/wp\/v2\/pages\/601","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/sites.nd.edu\/jianxun-wang\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/sites.nd.edu\/jianxun-wang\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/sites.nd.edu\/jianxun-wang\/wp-json\/wp\/v2\/users\/3220"}],"replies":[{"embeddable":true,"href":"https:\/\/sites.nd.edu\/jianxun-wang\/wp-json\/wp\/v2\/comments?post=601"}],"version-history":[{"count":8,"href":"https:\/\/sites.nd.edu\/jianxun-wang\/wp-json\/wp\/v2\/pages\/601\/revisions"}],"predecessor-version":[{"id":1101,"href":"https:\/\/sites.nd.edu\/jianxun-wang\/wp-json\/wp\/v2\/pages\/601\/revisions\/1101"}],"wp:attachment":[{"href":"https:\/\/sites.nd.edu\/jianxun-wang\/wp-json\/wp\/v2\/media?parent=601"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}