2 papers
physics.optics2026
TRON: Trainable, architecture-reconfigurable random optical neural networks
Ziao Wang, Fei Xia, Logan G. Wright +5
Deep learning has triggered explosive growth in the demand for specialized hardware processors, thus motivating the development of scalable and reconfigurable computing substrates.…
cs.LG2026
Training deep physical neural networks with local physical information bottleneck
Hao Wang, Ziao Wang, Xiangpeng Liang +8
Deep learning has revolutionized modern society but faces growing energy and latency constraints. Deep physical neural networks (PNNs) are interconnected computing systems that dir…