Enabling Multi-Robot Collaboration from Single-Human Guidance

Autor: Ji, Zhengran, Zhang, Lingyu, Sajda, Paul, Chen, Boyuan

Learning collaborative behaviors is essential for multi-agent systems. Traditionally, multi-agent reinforcement learning solves this implicitly through a joint reward and centralized observations, assuming collaborative behavior will emerge. Other st

Externí odkaz: http://arxiv.org/abs/2409.19831

Electron energy loss spectroscopy database synthesis and automation of core-loss edge recognition by deep-learning neural networks

Autor: Kong, Lingli, Ji, Zhengran, Xin, Huolin L.

The ionization edges encoded in the electron energy loss spectroscopy (EELS) spectra enable advanced material analysis including composition analyses and elemental quantifications. The development of the parallel EELS instrument and fast, sensitive d

Externí odkaz: http://arxiv.org/abs/2209.13026

Decoding Spatial Symmetry and EELS Spectroscopic Fine Structures.

Autor: Xin, Huolin L, Wang, Chunyang, Zhu, Dong, Ji, Zhengran, Hu, Mike, Kong, Lingli

Publikováno v: Microscopy & Microanalysis; 2023 Supplement, p1924-1924, 1p

Electron energy loss spectroscopy database synthesis and automation of core-loss edge recognition by deep-learning neural networks.

Autor: Kong L; Department of Physics, University of California, Irvine, CA, 92617, USA., Ji Z; Department of Physics, University of California, Irvine, CA, 92617, USA., Xin HL; Department of Physics, University of California, Irvine, CA, 92617, USA. huolin.xin@uci.edu.

Publikováno v: Scientific reports [Sci Rep] 2022 Dec 23; Vol. 12 (1), pp. 22183. Date of Electronic Publication: 2022 Dec 23.