14 citations · 24 across the 6 of their papers we have counts for
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cs.LG2024
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…
cond-mat.mtrl-sci2024★ 14 cited
CrystalFlow: A Flow-Based Generative Model for Crystalline Materials
Xiaoshan Luo, Zhenyu Wang, Qingchang Wang +4
Deep learning-based generative models have emerged as powerful tools for modeling complex data distributions and generating high-fidelity samples, offering a transformative approac…
cond-mat.mtrl-sci2024★ 7 cited
Space Group Informed Transformer for Crystalline Materials Generation
Zhendong Cao, Xiaoshan Luo, Jian Lv +1
We introduce CrystalFormer, a transformer-based autoregressive model specifically designed for space group-controlled generation of crystalline materials. By explicitly incorporati…