Jonathan Heek

Artificial Intelligence · 2019–2023

A researcher in the Science corpus: 6 papers; trusts 137 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 126 citations into it
• Computer Vision and Pattern Recognition — 125 citations into it
• Model Architectures — 36 citations into it
• Efficiency & Compression — 34 citations into it
• Generative Models — 28 citations into it
• Optimization & Training — 15 citations into it
• Probabilistic & Bayesian Methods — 13 citations into it
• Signal Processing — 11 citations into it

Whom Jonathan Heek trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Kaiming He
4. Max Welling
5. Tim Salimans
6. Alex Krizhevsky
7. Sergey Ioffe
8. Yoshua Bengio
9. Jonathan Ho
10. Ilya Sutskever

Who trusts Jonathan Heek overall

1. Michael W. Dusenberry
2. Yang Song
3. Ghassen Jerfel
4. Shekoofeh Azizi
5. Anthony Hu

Papers from Jonathan Heek's perspective

Ordered by how strongly the researchers Jonathan Heek trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Scaling Vision Transformers to 22 Billion Parameters (2023) — 911 citations
• Efficiently Scaling Transformer Inference (2022) — 688 citations
• MetNet: A Neural Weather Model for Precipitation Forecasting (2020) — 361 citations
• Skillful Twelve Hour Precipitation Forecasts using Large Context Neural Networks (2021) — 55 citations
• Bayesian Inference for Large Scale Image Classification (2019) — 38 citations
• simple diffusion: End-to-end diffusion for high resolution images (2023) — 453 citations