24 citations · 32 across the 16 of their papers we have counts for
4 papers · 1 filter
TagBO: LLM-Driven Task-Aware Graph Bayesian Optimization for Scientific Discovery
Xinzhe Yuan, Zimu Zeng, Zhuo Chen +6
Mixed-variable optimization in scientific discovery often requires exploring large combinatorial spaces under costly experimental evaluations, making sample?efficient Bayesian opti…
LABO: LLM-Accelerated Bayesian Optimization through Broad Exploration and Selective Experimentation
Zhuo Chen, Xinzhe Yuan, Jianshu Zhang +8
The high cost and data scarcity in scientific exploration have motivated the use of large language models (LLMs) as knowledge-driven components in Bayesian optimization (BO). Howev…
Synergistic Development of Perovskite Memristors and Algorithms for Robust Analog Computing
Nanyang Ye, Qiao Sun, Yifei Wang +10
Analog computing using non-volatile memristors has emerged as a promising solution for energy-efficient deep learning. New materials, like perovskites-based memristors are recently…
Domain Invariant Learning for Gaussian Processes and Bayesian Exploration
Xilong Zhao, Siyuan Bian, Yaoyun Zhang +5
Out-of-distribution (OOD) generalization has long been a challenging problem that remains largely unsolved. Gaussian processes (GP), as popular probabilistic model classes, especia…