Junwhan Ahn
Artificial Intelligence · 2015–2023
A researcher in the Science corpus: 4 papers; trusts 111 researchers and is trusted by 10 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 128 citations into it; #15,312 of 35,345 by trust here, #6,468 by citations
- Computer Vision and Pattern Recognition — 58 citations into it; #9,813 of 21,575 by trust here, #9,305 by citations
- Natural Language Processing — 56 citations into it
- Evaluation & Benchmarks — 43 citations into it
- Hardware and Architecture — 37 citations into it; #1,416 of 1,551 by trust here, #494 by citations
- Computer Networks and Communications — 28 citations into it; #9,370 of 9,886 by trust here, #3,318 by citations
- Efficiency & Compression — 10 citations into it; #555 of 1,264 by trust here, #925 by citations
- Model Architectures — 8 citations into it
Whom Junwhan Ahn trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Sungpack Hong
- Kaiming He
- Alex Krizhevsky
- Ilya Sutskever
- Onur Mutlu
- Geoffrey E. Hinton
- Shaoqing Ren
- Chi-Keung Luk
- Tayo Oguntebi
- Yoshua Bengio
Who trusts Junwhan Ahn overall
- Onur Mutlu
- Shuangchen Li
- Yunhui Guo
- Jungwook Choi
- Saugata Ghose
- Frederick Tung
- Mingyu Gao
- Tae Jun Ham
- Amirali Boroumand
- Assi Barak
Papers from Junwhan Ahn's perspective
Ordered by how strongly the researchers Junwhan Ahn trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Going deeper with convolutions
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- ImageNet Large Scale Visual Recognition Challenge
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- PaLM 2 Technical Report (2023) — 1,524 citations
- Weighted-Entropy-Based Quantization for Deep Neural Networks (2017) — 272 citations
- PIM-enabled instructions: A low-overhead, locality-aware processing-in-memory architecture (2015) — 543 citations
- A scalable processing-in-memory accelerator for parallel graph processing (2015) — 900 citations