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2020 – today
- 2024
[c12]Seongmin Hong, Kyeonghyun Lee, Suh Yoon Jeon, Hyewon Bae, Se Young Chun:
On Exact Inversion of DPM-Solvers. CVPR 2024: 7069-7078- [i9]Seungjae Moon, Jung-Hoon Kim, Junsoo Kim, Seongmin Hong, Junseo Cha, Minsu Kim, Sukbin Lim, Gyubin Choi, Dongjin Seo, Jongho Kim, Hunjong Lee, Hyunjun Park, Ryeowook Ko, Soongyu Choi, Jongse Park, Jinwon Lee, Joo-Young Kim:
LPU: A Latency-Optimized and Highly Scalable Processor for Large Language Model Inference. CoRR abs/2408.07326 (2024) - [i8]Seongmin Hong, Jaehyeok Bae, Jongho Lee, Se Young Chun:
Adaptive Selection of Sampling-Reconstruction in Fourier Compressed Sensing. CoRR abs/2409.11738 (2024) - [i7]Seongmin Hong, Suh Yoon Jeon, Kyeonghyun Lee, Ernest K. Ryu, Se Young Chun:
Gradient-free Decoder Inversion in Latent Diffusion Models. CoRR abs/2409.18442 (2024) - 2023
- [j2]Prasetiyo
, Seongmin Hong, Yashael Faith Arthanto, Joo-Young Kim:
Accelerating Deep Convolutional Neural Networks Using Number Theoretic Transform. IEEE Trans. Circuits Syst. I Regul. Pap. 70(1): 315-326 (2023) - [c11]Seongmin Hong, Se Young Chun:
Neural Diffeomorphic Non-uniform B-spline Flows. AAAI 2023: 12225-12233 - [c10]Seungjae Moon, Junsoo Kim, Jung-Hoon Kim, Junseo Cha, Gyubin Choi, Seongmin Hong, Joo-Young Kim:
HyperAccel Latency Processing Unit (LPUTM) Accelerating Hyperscale Models for Generative AI. HCS 2023: 1 - [c9]Seongmin Hong, Inbum Park, Se Young Chun:
On the Robustness of Normalizing Flows for Inverse Problems in Imaging. ICCV 2023: 10711-10721 - [i6]Seongmin Hong, Se Young Chun:
Neural Diffeomorphic Non-uniform B-spline Flows. CoRR abs/2304.04555 (2023) - [i5]Seongmin Hong, Kyeonghyun Lee, Suh Yoon Jeon, Hyewon Bae, Se Young Chun:
On Exact Inversion of DPM-Solvers. CoRR abs/2311.18387 (2023) - 2022
- [j1]Inho Lee, Yangki Lee, Hongjun Um, Seongmin Hong, Yongjun Park:
Dynamic Rate Neural Acceleration Using Multiprocessing Mode Support. IEEE Trans. Very Large Scale Integr. Syst. 30(10): 1461-1472 (2022) - [c8]Andrey Ignatov, Grigory Malivenko, Radu Timofte, Lukasz Treszczotko, Xin Chang, Piotr Ksiazek, Michal Lopuszynski, Maciej Pioro, Rafal Rudnicki, Maciej Smyl, Yujie Ma, Zhenyu Li, Zehui Chen, Jialei Xu, Xianming Liu, Junjun Jiang, XueChao Shi, Difan Xu, Yanan Li, Xiaotao Wang, Lei Lei, Ziyu Zhang, Yicheng Wang, Zilong Huang, Guozhong Luo, Gang Yu, Bin Fu, Jiaqi Li, Yiran Wang, Zihao Huang, Zhiguo Cao, Marcos V. Conde, Denis Sapozhnikov, Byeong Hyun Lee, Dongwon Park, Seongmin Hong, Joonhee Lee, Seunggyu Lee, Se Young Chun:
Efficient Single-Image Depth Estimation on Mobile Devices, Mobile AI & AIM 2022 Challenge: Report. ECCV Workshops (3) 2022: 71-91 - [c7]Andrey Ignatov, Radu Timofte, Maurizio Denna, Abdel Younes, Ganzorig Gankhuyag, Jingang Huh, Myeong Kyun Kim, Kihwan Yoon, Hyeon-Cheol Moon, Seungho Lee, Yoonsik Choe, Jinwoo Jeong, Sungjei Kim, Maciej Smyl, Tomasz Latkowski, Pawel Kubik, Michal Sokolski, Yujie Ma, Jiahao Chao, Zhou Zhou, Hongfan Gao, Zhengfeng Yang, Zhenbing Zeng, Zhengyang Zhuge, Chenghua Li, Dan Zhu, Mengdi Sun, Ran Duan, Yan Gao, Lingshun Kong, Long Sun, Xiang Li, Xingdong Zhang, Jiawei Zhang, Yaqi Wu, Jinshan Pan, Gaocheng Yu, Jin Zhang, Feng Zhang, Zhe Ma, Hongbin Wang, Hojin Cho, Steve Kim, Huaen Li, Yanbo Ma, Ziwei Luo, Youwei Li, Lei Yu, Zhihong Wen, Qi Wu, Haoqiang Fan, Shuaicheng Liu, Lize Zhang, Zhikai Zong, Jeremy Kwon, Junxi Zhang, Mengyuan Li, Nianxiang Fu, Guanchen Ding, Han Zhu, Zhenzhong Chen, Gen Li, Yuanfan Zhang, Lei Sun, Dafeng Zhang, Neo Yang, Fitz Liu, Jerry Zhao, Mustafa Ayazoglu, Bahri Batuhan Bilecen, Shota Hirose, Kasidis Arunruangsirilert, Luo Ao, Ho Chun Leung, Andrew Wei, Jie Liu, Qiang Liu, Dahai Yu, Ao Li, Lei Luo, Ce Zhu, Seongmin Hong, Dongwon Park, Joonhee Lee, Byeong Hyun Lee, Seunggyu Lee, Se Young Chun, Ruiyuan He, Xuhao Jiang, Haihang Ruan, Xinjian Zhang, Jing Liu, Garas Gendy, Nabil Sabor, Jingchao Hou, Guanghui He:
Efficient and Accurate Quantized Image Super-Resolution on Mobile NPUs, Mobile AI & AIM 2022 Challenge: Report. ECCV Workshops (3) 2022: 92-129 - [c6]Seongmin Hong, Seungjae Moon, Junsoo Kim, Sungjae Lee, Minsub Kim, Dongsoo Lee, Joo-Young Kim:
DFX: A Low-latency Multi-FPGA Appliance for Accelerating Transformer-based Text Generation. HCS 2022: 1-17 - [c5]Seongmin Hong, Seungjae Moon, Junsoo Kim, Sungjae Lee, Minsub Kim, Dongsoo Lee, Joo-Young Kim:
DFX: A Low-latency Multi-FPGA Appliance for Accelerating Transformer-based Text Generation. MICRO 2022: 616-630 - [i4]Seongmin Hong, Seungjae Moon, Junsoo Kim, Sungjae Lee, Minsub Kim, Dongsoo Lee, Joo-Young Kim:
DFX: A Low-latency Multi-FPGA Appliance for Accelerating Transformer-based Text Generation. CoRR abs/2209.10797 (2022) - [i3]Andrey Ignatov, Grigory Malivenko, Radu Timofte, Lukasz Treszczotko, Xin Chang, Piotr Ksiazek, Michal Lopuszynski, Maciej Pioro, Rafal Rudnicki, Maciej Smyl, Yujie Ma, Zhenyu Li, Zehui Chen, Jialei Xu, Xianming Liu, Junjun Jiang, XueChao Shi, Difan Xu, Yanan Li, Xiaotao Wang, Lei Lei, Ziyu Zhang, Yicheng Wang, Zilong Huang, Guozhong Luo, Gang Yu, Bin Fu, Jiaqi Li, Yiran Wang, Zihao Huang, Zhiguo Cao, Marcos V. Conde, Denis Sapozhnikov, Byeong Hyun Lee, Dongwon Park, Seongmin Hong, Joonhee Lee, Seunggyu Lee, Se Young Chun:
Efficient Single-Image Depth Estimation on Mobile Devices, Mobile AI & AIM 2022 Challenge: Report. CoRR abs/2211.04470 (2022) - [i2]Seongmin Hong, Inbum Park, Se Young Chun:
On the Robustness of Normalizing Flows for Inverse Problems in Imaging. CoRR abs/2212.04319 (2022) - 2021
- [c4]Je Yang, Seongmin Hong, Joo-Young Kim:
FIXAR: A Fixed-Point Deep Reinforcement Learning Platform with Quantization-Aware Training and Adaptive Parallelism. DAC 2021: 259-264 - [i1]Je Yang, Seongmin Hong, Joo-Young Kim:
FIXAR: A Fixed-Point Deep Reinforcement Learning Platform with Quantization-Aware Training and Adaptive Parallelism. CoRR abs/2102.12103 (2021)
2010 – 2019
- 2018
- [c3]Seongmin Hong, Inho Lee, Yongjun Park:
NN compactor: Minimizing memory and logic resources for small neural networks. DATE 2018: 581-584 - [c2]Inho Lee, Seongmin Hong, Giha Ryu, Yongjun Park:
Automated Neural Network Accelerator Generation Framework for Multiple Neural Network Applications. TENCON 2018: 2287-2290 - 2017
- [c1]Seongmin Hong, Yongjun Park:
A FPGA-based neural accelerator for small IoT devices. ISOCC 2017: 294-295
Coauthor Index
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