AI for Scientists: Accelerating Discovery through Knowledge, Data and Learning
Neurosymbolic Programming for Science via YouTube
Overview
Explore a 54-minute conference talk on AI applications in scientific research, focusing on scientist-in-the-loop frameworks that bridge machine learning and real-world use cases. Discover how these models accommodate varying data, analysis tasks, and existing domain knowledge while optimizing expert effort in scientific workflows. Learn about methods for discovering semantically meaningful structure from data and integrating domain knowledge with learning. Gain insights into the speaker's collaborative approach with scientists to accelerate scientific progress through efficient AI-driven techniques.
Syllabus
AI for Scientists: Accelerating Discovery through Knowledge, Data & Learning
Taught by
Neurosymbolic Programming for Science