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DTSTAMP:20260610T024313Z
DESCRIPTION:Accuracy and Efficiency in Scientific Machine Learning\n\n\n	IVA
 DO and the Montreal Mathematical Research Center are pleased to welcome so
 me twenty international experts in the field of physics-informed machine l
 earning who will share their latest advances in the mathematical analysis 
 of methods using Neural Networks. Despite ongoing efforts to integrate mac
 hine learning techniques into computer simulations\, significant challenge
 s remain in developing accurate and efficient SciML methodologies for rout
 ine use in science and engineering applications.\n\n	The workshop aims to a
 ddress these challenges by creating novel mathematical theories for error 
 estimation and control. These developments are intended to improve the acc
 uracy and efficiency of Neural Network approximations for initial- and bou
 ndary-value problems and operator learning.\n\n	During the workshop\, stude
 nts\, postdocs\, and researchers will have multiple opportunities for disc
 ussions with scientific leaders on these issues. A poster session and an i
 nformal cocktail reception are also on the agenda.\n\n	We encourage you\, a
 s well as your collaborators and students\, to present your work during th
 e poster session and to take this opportunity to engage in discussions wit
 h our guests and gain new perspectives.\n\n	Click HERE to register.\n\n\n 
 \n
DTSTART;VALUE=DATE:20250625
DTEND;VALUE=DATE:20250627
SUMMARY:Accuracy and Efficiency in Scientific Machine Learning
URL:https://www.mcgill.ca/mathstat/channels/event/accuracy-and-efficiency-s
 cientific-machine-learning-365818
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