Alexander J. Smola

Artificial Intelligence · with Zhang · 2020–2023

A researcher in the Science corpus: 3 papers; trusts 192 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 150 citations into it; #20,676 of 35,345 by trust here, #9,092 by citations
• Computer Vision and Pattern Recognition — 88 citations into it
• Natural Language Processing — 48 citations into it; #4,058 of 5,688 by trust here, #3,053 by citations
• Information Systems — 22 citations into it
• Representation & Self-Supervised Learning — 13 citations into it

Whom Alexander J. Smola trusts overall

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

1. Geoffrey E. Hinton
2. Ross B. Girshick
3. Yoshua Bengio
4. Alex Krizhevsky
5. Yann LeCun
6. Kaiming He
7. David G. Lowe
8. Diederik P. Kingma
9. Ilya Sutskever
10. Christian Szegedy

Who trusts Alexander J. Smola overall

1. Kevin Chen-Chuan Chang
2. Jie Huang
3. Erica Schmidt
4. Maithra Raghu
5. Davood Rafiei
6. M. Pourreza

Papers from Alexander J. Smola's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Attention is All you Need (Neural Information Processing Systems)
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Going deeper with convolutions
9. ImageNet Large Scale Visual Recognition Challenge
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• Multimodal Chain-of-Thought Reasoning in Language Models (2023) — 914 citations
• Automatic Chain of Thought Prompting in Large Language Models (2022) — 1,007 citations
• Dive into Deep Learning (2020) — 682 citations