{"id":160,"date":"2023-05-01T12:00:33","date_gmt":"2023-05-01T16:00:33","guid":{"rendered":"https:\/\/carleton.ca\/richarddansereau\/?p=160"},"modified":"2025-12-08T12:15:59","modified_gmt":"2025-12-08T17:15:59","slug":"youhau-yu-defends-his-phd-thesis","status":"publish","type":"post","link":"https:\/\/carleton.ca\/richarddansereau\/2023\/youhau-yu-defends-his-phd-thesis\/","title":{"rendered":"Youhao Yu defends his PhD thesis:"},"content":{"rendered":"<table style=\"border-collapse: collapse; width: 100%;\">\n<tbody>\n<tr>\n<td style=\"width: 30%;\"><img decoding=\"async\" loading=\"lazy\" class=\"alignnone size-medium wp-image-166\" src=\"https:\/\/carleton.ca\/richarddansereau\/wp-content\/uploads\/Youhao-1-2-240x85.png\" alt=\"\" width=\"240\" height=\"85\" srcset=\"https:\/\/carleton.ca\/richarddansereau\/wp-content\/uploads\/Youhao-1-2-240x85.png 240w, https:\/\/carleton.ca\/richarddansereau\/wp-content\/uploads\/Youhao-1-2-400x142.png 400w, https:\/\/carleton.ca\/richarddansereau\/wp-content\/uploads\/Youhao-1-2-160x57.png 160w, https:\/\/carleton.ca\/richarddansereau\/wp-content\/uploads\/Youhao-1-2-768x273.png 768w, https:\/\/carleton.ca\/richarddansereau\/wp-content\/uploads\/Youhao-1-2-360x128.png 360w, https:\/\/carleton.ca\/richarddansereau\/wp-content\/uploads\/Youhao-1-2.png 800w\" sizes=\"(max-width: 240px) 100vw, 240px\" \/><\/td>\n<td style=\"width: 70%;\">\n<h3>Youhao successfully defended his PhD thesis<\/h3>\n<blockquote>\n<h4><b>Reconstruction of Compressive Sensed (CS) Images with Deep Equilibrium Model (DEQ) Based on Iterative Shrinkage-Thresholding Algorithm (ISTA).<\/b><\/h4>\n<\/blockquote>\n<p>In this thesis, we explored using learned compressive sensing for image compression using a deep neural network in the form of a deep equilibrium model (DEQ) as an alternative to the deep unrolling of more traditional iterative shrinkage-thresholding algorithm (ISTA). The advantage of the approach is a neural network that can speed up compressive sensing reconstruction using a fixed-point iterative approach and semi-tensor product (STP) decompositions cast in a neural network.<\/p>\n<p>Congratulations Youhao Yu!<\/td>\n<\/tr>\n<\/tbody>\n<\/table>\n<p><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Youhao successfully defended his PhD thesis Reconstruction of Compressive Sensed (CS) Images with Deep Equilibrium Model (DEQ) Based on Iterative Shrinkage-Thresholding Algorithm (ISTA). In this thesis, we explored using learned compressive sensing for image compression using a deep neural network in the form of a deep equilibrium model (DEQ) as an alternative to the deep [&hellip;]<\/p>\n","protected":false},"author":6,"featured_media":0,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_relevanssi_hide_post":"","_relevanssi_hide_content":"","_relevanssi_pin_for_all":"","_relevanssi_pin_keywords":"","_relevanssi_unpin_keywords":"","_relevanssi_related_keywords":"","_relevanssi_related_include_ids":"","_relevanssi_related_exclude_ids":"","_relevanssi_related_no_append":"","_relevanssi_related_not_related":"","_relevanssi_related_posts":"","_relevanssi_noindex_reason":"","_mi_skip_tracking":false,"_exactmetrics_sitenote_active":false,"_exactmetrics_sitenote_note":"","_exactmetrics_sitenote_category":0,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"footnotes":"","_links_to":"","_links_to_target":""},"categories":[22,1],"tags":[],"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v21.2 - https:\/\/yoast.com\/wordpress\/plugins\/seo\/ -->\n<title>Youhao Yu defends his PhD thesis: - Prof. Richard M. 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