FIXAR: A Fixed-Point Deep Reinforcement Learning Platform with Quantization-Aware Training and Adaptive Parallelism. - Je Yang; Seongmin Hong; Joo-Young Kim 001 (DAC, 2021)

LearningGroup: A Real-Time Sparse Training on FPGA via Learnable Weight Grouping for Multi-Agent Reinforcement Learning. - Je Yang; Jaeuk Kim; Joo-Young Kim 001 (FPT, 2022)

JNPU: A 1.04TFLOPS Joint-DNN Training Processor with Speculative Cyclic Quantization and Triple Heterogeneity on Microarchitecture / Precision / Dataflow. - Je Yang; Sukbin Lim; Sukjin Lee; Jae-Young Kim; Joo-Young Kim 001 (ESSCIRC, 2023)