4 citations · 6 across the 3 of their papers we have counts for
3 papers
cs.LG2023★ 1 cited
Cross-Episodic Curriculum for Transformer Agents
Lucy Xiaoyang Shi, Yunfan Jiang, Jake Grigsby +2
We present a new algorithm, Cross-Episodic Curriculum (CEC), to boost the learning efficiency and generalization of Transformer agents. Central to CEC is the placement of cross-epi…
cs.LG2023★ 1 cited
PGrad: Learning Principal Gradients For Domain Generalization
Zhe Wang, Jake Grigsby, Yanjun Qi
Machine learning models fail to perform when facing out-of-distribution (OOD) domains, a challenging task known as domain generalization (DG). In this work, we develop a novel DG t…
hep-ph2022★ 4 cited
Benchmarks for a Global Extraction of Information from Deeply Virtual Exclusive Scattering
Manal Almaeen, Jake Grigsby, Joshua Hoskins +4
We develop a framework to establish benchmarks for machine learning and deep neural networks analyses of exclusive scattering cross sections (FemtoNet). Within this framework we pr…