Seminar • Artificial Intelligence • Learning Generative Models from a Control Perspective for Scientific Discovery
Please note: This seminar will take place in DC 1304.
Dinghuai Zhang, PhD candidate
Mila
Advancements in scientific discovery have always been at the forefront of human endeavor, particularly in complex domains such as molecule synthesis. The intrinsic challenges in these fields stem from two main factors: the vast and combinatorially complex high-dimensional search spaces, and the costly evaluation of scientific hypotheses. Therefore, leveraging machine learning offers a promising avenue to expedite the scientific discovery process.