9 citations · 14 across the 5 of their papers we have counts for
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physics.optics2024★ 2 cited
Perfecting Imperfect Physical Neural Networks with Transferable Robustness using Sharpness-Aware Training
Tengji Xu, Zeyu Luo, Shaojie Liu +5
AI models are essential in science and engineering, but recent advances are pushing the limits of traditional digital hardware. To address these limitations, physical neural networ…
physics.optics2024★ 9 cited
High-precision programming of large-scale ring resonator circuits with minimal pre-calibration
Shaojie Liu, Tengji Xu, Benshan Wang +3
Microring resonators (MRRs) are essential components in large-scale photonic integrated circuits (PICs), but programming these circuits with high precision and efficiency remains a…
physics.optics2024★ 1 cited
Control-free and efficient integrated photonic neural networks via hardware-aware training and pruning
Tengji Xu, Weipeng Zhang, Jiawei Zhang +8
Integrated photonic neural networks (PNNs) are at the forefront of AI computing, leveraging on light's unique properties, such as large bandwidth, low latency, and potentially low…