Physics-Informed Deep Learning - Learning from Small Data

Explore a comprehensive presentation on 'Physics-Informed Deep Learning: Learning from Small Data' delivered by Lu Lu from the University of Pennsylvania. Recorded during the weekly DataLearning working group meeting on May 31, 2022, this 57-minute talk delves into innovative techniques for leveraging small datasets in deep learning applications with physics-based constraints. Gain insights into the interdisciplinary research conducted by the DataLearning group, which focuses on developing cutting-edge technologies that combine Data Assimilation and Machine Learning. Discover how physics-informed approaches can enhance deep learning models' performance and interpretability, especially in scenarios with limited data availability. Suitable for researchers, students, and professionals interested in the intersection of physics, machine learning, and data science.