1 citations · 1 across the 5 of their papers we have counts for
6 papers
Homodyne Photonic Tensor Processor exceeds 1,000-TOPS
Lian Zhou, Kaiwen Xue, Yun-Jhu Lee +10
High-performance computing underpins modern artificial intelligence (AI), enabling foundation models, real-time inference and perception in autonomous systems, and data-intensive s…
Quantization-aware Photonic Homodyne computing for Accelerated Artificial Intelligence and Scientific Simulation
Lian Zhou, Kaiwen Xue, Amirhossein Fallah +14
Modern problems in high-performance computing, ranging from training and inferencing deep learning models in computer vision and language models to simulating complex physical syst…
Tortoise and Hare Guidance: Accelerating Diffusion Model Inference with Multirate Integration
Yunghee Lee, Byeonghyun Pak, Junwha Hong +1
In this paper, we propose Tortoise and Hare Guidance (THG), a training-free strategy that accelerates diffusion sampling while maintaining high-fidelity generation. We demonstrate…
Experimental Demonstration of Imperfection-Agnostic Local Learning Rules on Photonic Neural Networks with Mach-Zehnder Interferometric Meshes
Luis El Srouji, Mehmet Berkay On, Yun-Jhu Lee +2
Mach-Zehnder Interferometric meshes are attractive for low-loss photonic matrix multiplication but are challenging to program. Using least-squares optimization of directional deriv…
Scalable Nanophotonic-Electronic Spiking Neural Networks
Luis El Srouji, Yun-Jhu Lee, Mehmet Berkay On +2
Spiking neural networks (SNN) provide a new computational paradigm capable of highly parallelized, real-time processing. Photonic devices are ideal for the design of high-bandwidth…
Izhikevich-Inspired Optoelectronic Neurons with Excitatory and Inhibitory Inputs for Energy-Efficient Photonic Spiking Neural Networks
Yun-jhu Lee, Mehmet Berkay On, Xian Xiao +2
We designed, prototyped, and experimentally demonstrated, for the first time to our knowledge, an optoelectronic spiking neuron inspired by the Izhikevich model incorporating both…