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NeurOLight: A Physics-Agnostic Neural Operator Enabling Parametric Photonic Device Simulation


Sep 19, 2022
Jiaqi Gu, Zhengqi Gao, Chenghao Feng, Hanqing Zhu, Ray T. Chen, Duane S. Boning, David Z. Pan

* 13 pages. Accepted to NeurIPS 2022 

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TAG: Learning Circuit Spatial Embedding From Layouts


Sep 07, 2022
Keren Zhu, Hao Chen, Walker J. Turner, George F. Kokai, Po-Hsuan Wei, David Z. Pan, Haoxing Ren

* Accepted by ICCAD 2022 

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Delving into Effective Gradient Matching for Dataset Condensation


Jul 30, 2022
Zixuan Jiang, Jiaqi Gu, Mingjie Liu, David Z. Pan

* 12 pages 

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On-chip QNN: Towards Efficient On-Chip Training of Quantum Neural Networks


Feb 26, 2022
Hanrui Wang, Zirui Li, Jiaqi Gu, Yongshan Ding, David Z. Pan, Song Han

* Published as a conference paper in DAC 2022; 7 pages, 8 figures; open-source at https://github.com/mit-han-lab/torchquantum 

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ELight: Enabling Efficient Photonic In-Memory Neurocomputing with Life Enhancement


Dec 15, 2021
Hanqing Zhu, Jiaqi Gu, Chenghao Feng, Mingjie Liu, Zixuan Jiang, Ray T. Chen, David Z. Pan

* 7 pages, 8 figures, accepted by ASPDAC 2022 

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Multi-Scale High-Resolution Vision Transformer for Semantic Segmentation


Nov 23, 2021
Jiaqi Gu, Hyoukjun Kwon, Dilin Wang, Wei Ye, Meng Li, Yu-Hsin Chen, Liangzhen Lai, Vikas Chandra, David Z. Pan

* 8 pages 

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Silicon photonic subspace neural chip for hardware-efficient deep learning


Nov 11, 2021
Chenghao Feng, Jiaqi Gu, Hanqing Zhu, Zhoufeng Ying, Zheng Zhao, David Z. Pan, Ray T. Chen

* 17 pages,3 figures 

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HRViT: Multi-Scale High-Resolution Vision Transformer


Nov 01, 2021
Jiaqi Gu, Hyoukjun Kwon, Dilin Wang, Wei Ye, Meng Li, Yu-Hsin Chen, Liangzhen Lai, Vikas Chandra, David Z. Pan

* 8 pages 

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L2ight: Enabling On-Chip Learning for Optical Neural Networks via Efficient in-situ Subspace Optimization


Oct 27, 2021
Jiaqi Gu, Hanqing Zhu, Chenghao Feng, Zixuan Jiang, Ray T. Chen, David Z. Pan

* 10 pages. Accepted to NeurIPS 2021 

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RoQNN: Noise-Aware Training for Robust Quantum Neural Networks


Oct 21, 2021
Hanrui Wang, Jiaqi Gu, Yongshan Ding, Zirui Li, Frederic T. Chong, David Z. Pan, Song Han

* 19 pages, 10 figures, open-source at https://github.com/mit-han-lab/pytorch-quantum 

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