Shaked Brody

Artificial Intelligence · 2018–2022

A researcher in the Science corpus: 4 papers; trusts 205 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 205 citations into it; #28,920 of 35,345 by trust here, #31,361 by citations
• Natural Language Processing — 118 citations into it; #2,512 of 5,688 by trust here, #2,695 by citations
• Computer Vision and Pattern Recognition — 60 citations into it; #17,748 of 21,575 by trust here, #19,766 by citations
• Information Systems — 44 citations into it
• Model Architectures — 37 citations into it
• Graph Learning — 25 citations into it
• Representation & Self-Supervised Learning — 18 citations into it
• Code Generation & Program Synthesis — 14 citations into it

Whom Shaked Brody trusts overall

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

1. Miltiadis Allamanis
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Diederik P. Kingma
5. Ilya Sutskever
6. Dzmitry Bahdanau
7. Alex Krizhevsky
8. Oriol Vinyals
9. Sepp Hochreiter
10. Kaiming He

Who trusts Shaked Brody overall

1. Uri Alon
2. Yi Liao
3. Roei Schuster
4. Tess E. Smidt
5. Toufique Ahmed
6. Yichen Xu
7. Goutham Ramakrishnan
8. Roy Sadaka
9. Miltiadis Allamanis
10. Patrick Fernandes

Papers from Shaked Brody's perspective

Ordered by how strongly the researchers Shaked Brody 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. 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. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers

• BLOOM: A 176B-Parameter Open-Access Multilingual Language Model (2022) — 2,975 citations
• How Attentive are Graph Attention Networks? (2021) — 1,922 citations
• Neural Edit Completion (2020) — 7 citations
• code2seq: Generating Sequences from Structured Representations of Code (2018) — 812 citations