1 citations · 1 across the 2 of their papers we have counts for
2 papers
cs.AI2026
Towards Trustworthy Physical AI: From Theory to Practice Across Life Cycle
Wang Yang, Hongxuan Liu, Xinghui Xu +29
Physical AI refers to AI systems that understand, reason about, and act in accordance with the physical world and its underlying laws, dynamics, and constraints. Unlike conventiona…
cs.LG2023★ 1 cited
Automating reward function configuration for drug design
Marius Urbonas, Temitope Ajileye, Paul Gainer +1
Designing reward functions that guide generative molecular design (GMD) algorithms to desirable areas of chemical space is of critical importance in AI-driven drug discovery. Tradi…