Jeremiah Harmsen
Artificial Intelligence · 2014–2025
A researcher in the Science corpus: 8 papers; trusts 224 researchers and is trusted by 1 researcher here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 133 citations into it; #34,825 of 35,345 by trust here, #3,907 by citations
- Computer Vision and Pattern Recognition — 129 citations into it
- Model Architectures — 23 citations into it
- Information Systems — 18 citations into it; #8,479 of 8,771 by trust here, #480 by citations
- Information Retrieval & Search — 6 citations into it
Whom Jeremiah Harmsen trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Kaiming He
- Geoffrey E. Hinton
- Alex Krizhevsky
- Diederik P. Kingma
- Ross B. Girshick
- Yoshua Bengio
- Ilya Sutskever
- Yann LeCun
- Karen Simonyan
- Thorsten Joachims
Who trusts Jeremiah Harmsen overall
Papers from Jeremiah Harmsen's perspective
Ordered by how strongly the researchers Jeremiah Harmsen 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)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Long Short-Term Memory
- ImageNet Large Scale Visual Recognition Challenge
- Gradient-based learning applied to document recognition
- Going deeper with convolutions
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Scaling Vision Transformers to 22 Billion Parameters (2023) — 911 citations
- UViM: A Unified Modeling Approach for Vision with Learned Guiding Codes (2022) — 84 citations
- Up next: retrieval methods for large scale related video suggestion (2014) — 39 citations
- Wide & Deep Learning for Recommender Systems (2016) — 4,198 citations
- TensorFlow-Serving: Flexible, High-Performance ML Serving (2017) — 362 citations
- SigLIP 2: Multilingual Vision-Language Encoders with Improved Semantic Understanding, Localization, and Dense Features (2025) — 1,063 citations
- PaliGemma: A versatile 3B VLM for transfer (2024) — 728 citations
- RLDS: an Ecosystem to Generate, Share and Use Datasets in Reinforcement Learning (2021) — 42 citations