Moshe Wasserblat

Artificial Intelligence · 2019–2022

A researcher in the Science corpus: 2 papers; trusts 17 researchers and is trusted by 16 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 33 citations into it
• Natural Language Processing — 19 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it
• Representation & Self-Supervised Learning — 8 citations into it
• Model Architectures — 5 citations into it

Whom Moshe Wasserblat trusts overall

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

1. Yoshua Bengio
2. Karen Simonyan
3. Geoffrey E. Hinton
4. Jacob Devlin

Who trusts Moshe Wasserblat overall

1. Sehoon Kim
2. J. Scott McCarley

Papers from Moshe Wasserblat's perspective

Ordered by how strongly the researchers Moshe Wasserblat 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
4. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. ImageNet: A large-scale hierarchical image database
9. Gradient-based learning applied to document recognition
10. Distilling the Knowledge in a Neural Network (arXiv.org)

Their papers

• Efficient Few-Shot Learning Without Prompts (2022) — 311 citations
• Q8BERT: Quantized 8Bit BERT (2019) — 584 citations