Josh Abramson

Artificial Intelligence · 2018–2022

A researcher in the Science corpus: 5 papers; trusts 18 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 113 citations into it
• Reinforcement Learning — 76 citations into it
• Computer Vision and Pattern Recognition — 69 citations into it

Whom Josh Abramson trusts overall

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

1. Diederik P. Kingma
2. Kaiming He
3. Geoffrey E. Hinton
4. Ross B. Girshick
5. Alex Krizhevsky
6. Yoshua Bengio
7. Alex Graves
8. Yann LeCun
9. Ilya Sutskever
10. Jimmy Ba

Who trusts Josh Abramson overall

1. Gabriel Recchia

Papers from Josh Abramson's perspective

Ordered by how strongly the researchers Josh Abramson 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. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. ImageNet Large Scale Visual Recognition Challenge
9. GENERATIVE ADVERSARIAL NETS
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Unsupervised Predictive Memory in a Goal-Directed Agent (2018) — 206 citations
• Imitating Interactive Intelligence (2020) — 74 citations
• Optimizing agent behavior over long time scales by transporting value (2018) — 139 citations
• A data-driven approach for learning to control computers (2022) — 128 citations
• Intra-agent speech permits zero-shot task acquisition (2022) — 10 citations