James Koppel

Artificial Intelligence · 2017–2022

A researcher in the Science corpus: 4 papers; trusts 28 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 44 citations into it
• Information Systems — 35 citations into it; #4,501 of 8,771 by trust here, #5,078 by citations
• Software — 24 citations into it; #616 of 1,227 by trust here, #636 by citations
• Natural Language Processing — 18 citations into it
• Code Generation & Program Synthesis — 17 citations into it
• Signal Processing — 11 citations into it
• Computational Theory and Mathematics — 6 citations into it
• Computer Networks and Communications — 6 citations into it

Whom James Koppel trusts overall

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

1. Jens Krinke
2. Veselin Raychev
3. Yoshua Bengio
4. Geoffrey E. Hinton
5. Ross Tate
6. Anh Tuan Nguyen
7. Raghavan Komondoor
8. Andrian Marcus
9. John Whaley
10. Sumit Gulwani

Who trusts James Koppel overall

1. Chun Xia
2. Julian Aron Prenner
3. Thibaud Lutellier
4. Max Willsey
5. Lingming Zhang
6. Ma Jin

Papers from James Koppel's perspective

Ordered by how strongly the researchers James Koppel 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. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Learning Multiple Layers of Features from Tiny Images
10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers

• Semantic code search via equational reasoning (2020) — 52 citations
• Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models (2022) — 2,561 citations
• A large-scale benchmark for few-shot program induction and synthesis (2021) — 20 citations
• QuixBugs: a multi-lingual program repair benchmark set based on the quixey challenge (2017) — 324 citations