3 citations · 3 across the 10 of their papers we have counts for
4 papers · 1 filter
Towards a Generalizable AI for Materials Discovery: Validation through Immersion Coolant Screening
Hyunseung Kim, Dae-Woong Jeong, Changyoung Park +11
Artificial intelligence (AI) has emerged as a powerful accelerator of materials discovery, yet most existing models remain problem-specific, requiring additional data collection an…
ORCA: ORchestrating Causal Agent
Joanie Hayoun Chung, Sumin Lee, Sungbin Lim
Causal analysis on relational databases is challenging, as analysis datasets must be repeatedly queried from complex schemas. Recent LLM systems can automate individual steps, but…
Score-informed Neural Operator for Enhancing Ordering-based Causal Discovery
Jiyeon Kang, Songseong Kim, Chanhui Lee +6
Ordering-based approaches to causal discovery identify topological orders of causal graphs, providing scalable alternatives to combinatorial search methods. Under the Additive Nois…
Geometric Embedding Alignment via Curvature Matching in Transfer Learning
Sung Moon Ko, Jaewan Lee, Sumin Lee +3
Geometrical interpretations of deep learning models offer insightful perspectives into their underlying mathematical structures. In this work, we introduce a novel approach that le…