FlexGibbs: Reconfigurable Parallel Gibbs Sampling Accelerator for Structured Graphs. - Glenn G. Ko; Yuji Chai; Rob A. Rutenbar; David Brooks 001; Gu-Yeon Wei (FCCM, 2019)

Accelerating Bayesian Inference on Structured Graphs Using Parallel Gibbs Sampling. - Glenn G. Ko; Yuji Chai; Rob A. Rutenbar; David Brooks 001; Gu-Yeon Wei (FPL, 2019)

A Scalable Bayesian Inference Accelerator for Unsupervised Learning. - Glenn G. Ko; Yuji Chai; Marco Donato; Paul N. Whatmough; Thierry Tambe; Rob A. Rutenbar; Gu-Yeon Wei; David Brooks 001 (Hot Chips Symposium, 2020)

A 3mm2 Programmable Bayesian Inference Accelerator for Unsupervised Machine Perception using Parallel Gibbs Sampling in 16nm. - Glenn G. Ko; Yuji Chai; Marco Donato; Paul N. Whatmough; Thierry Tambe; Rob A. Rutenbar; David Brooks 001; Gu-Yeon Wei (VLSI Circuits, 2020)

SM6: A 16nm System-on-Chip for Accurate and Noise-Robust Attention-Based NLP Applications : The 33rd Hot Chips Symposium - August 22-24, 2021. - Thierry Tambe; En-Yu Yang; Glenn G. Ko; Yuji Chai; Coleman Hooper; Marco Donato; Paul N. Whatmough; Alexander M. Rush; David Brooks 001; Gu-Yeon Wei (HCS, 2021)

9.8 A 25mm2 SoC for IoT Devices with 18ms Noise-Robust Speech-to-Text Latency via Bayesian Speech Denoising and Attention-Based Sequence-to-Sequence DNN Speech Recognition in 16nm FinFET. - Thierry Tambe; En-Yu Yang; Glenn G. Ko; Yuji Chai; Coleman Hooper; Marco Donato; Paul N. Whatmough; Alexander M. Rush; David Brooks 001; Gu-Yeon Wei (ISSCC, 2021)

CoopMC: Algorithm-Architecture Co-Optimization for Markov Chain Monte Carlo Accelerators. - Yuji Chai; Glenn G. Ko; Wei-Te Mark Ting; Luke Bailey; David Brooks 001; Gu-Yeon Wei (HPCA, 2022)

Bigger&Faster: Two-stage Neural Architecture Search for Quantized Transformer Models. - Yuji Chai; Luke Bailey; Yunho Jin; Matthew Karle; Glenn G. Ko (CoRR, 2022)

Late Breaking Results: Test Selection For RTL Coverage By Unsupervised Learning From Fast Functional Simulation. - Rongjian Liang; Nathaniel Ross Pinckney; Yuji Chai; Haoxin Ren; Brucek Khailany (DAC, 2023)

PerfSAGE: Generalized Inference Performance Predictor for Arbitrary Deep Learning Models on Edge Devices. - Yuji Chai; Devashree Tripathy; Chuteng Zhou; Dibakar Gope; Igor Fedorov; Ramon Matas Navarro; David Brooks 001; Gu-Yeon Wei; Paul N. Whatmough (CoRR, 2023)

INT2.1: Towards Fine-Tunable Quantized Large Language Models with Error Correction through Low-Rank Adaptation. - Yuji Chai; John Gkountouras; Glenn G. Ko; David Brooks 001; Gu-Yeon Wei (CoRR, 2023)

A 16-nm SoC for Noise-Robust Speech and NLP Edge AI Inference With Bayesian Sound Source Separation and Attention-Based DNNs. - Thierry Tambe; En-Yu Yang; Glenn G. Ko; Yuji Chai; Coleman Hooper; Marco Donato; Paul N. Whatmough; Alexander M. Rush; David Brooks 001; Gu-Yeon Wei (IEEE J. Solid State Circuits, 2023)

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices. - Yuji Chai; Mujin Kwen; David Brooks 001; Gu-Yeon Wei (CoRR, 2025)