Youngjae Min
Artificial Intelligence · 2022–2024
A researcher in the Science corpus: 3 papers; trusts 23 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 54 citations into it
- Computer Vision and Pattern Recognition — 23 citations into it
- Meta & Continual Learning — 18 citations into it
- Optimization & Training — 14 citations into it
- Computational Mechanics — 13 citations into it
- Scaling & Learning Theory — 10 citations into it
- Statistical and Nonlinear Physics — 6 citations into it
Whom Youngjae Min trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Navid Azizan
- Arthur Jacot
- Mehrdad Farajtabar
- Chunyuan Zhang
- Jaehoon Lee
- Apoorva Sharma
- Yuanzhi Li
- Huiyi Hu
- Matthew Brand
- Tianzong Yu
Who trusts Youngjae Min overall
Papers from Youngjae Min's perspective
Ordered by how strongly the researchers Youngjae Min trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Learning Multiple Layers of Features from Tiny Images
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Attention is All you Need (Neural Information Processing Systems)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)