2 citations · 5 across the 8 of their papers we have counts for
4 papers · 1 filter
Machine Intelligence on Wireless Edge Networks
Sri Krishna Vadlamani, Kfir Sulimany, Zhihui Gao +2
Machine intelligence on edge devices enables low-latency processing and improved privacy, but is often limited by the energy and delay of moving and converting data. Current system…
Disaggregated Deep Learning via In-Physics Computing at Radio Frequency
Zhihui Gao, Sri Krishna Vadlamani, Kfir Sulimany +2
Modern edge devices, such as cameras, drones, and Internet-of-Things nodes, rely on deep learning to enable a wide range of intelligent applications, including object recognition,…
QAMNet: Fast and Efficient Optical QAM Neural Networks
Marc Gong Bacvanski, Sri Krishna Vadlamani, Kfir Sulimany +1
The energy consumption of neural network inference has become a topic of paramount importance with the growing success and adoption of deep neural networks. Analog optical neural n…
Transferable Learning on Analog Hardware
Sri Krishna Vadlamani, Dirk Englund, Ryan Hamerly
While analog neural network (NN) accelerators promise massive energy and time savings, an important challenge is to make them robust to static fabrication error. Present-day traini…