Thomas Manzini

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 50 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 42 citations into it
• Computer Vision and Pattern Recognition — 32 citations into it
• Natural Language Processing — 24 citations into it; #3,432 of 5,688 by trust here, #2,473 by citations
• Representation & Self-Supervised Learning — 11 citations into it
• Multimodal Learning — 10 citations into it
• Experimental and Cognitive Psychology — 8 citations into it
• Safety, Robustness & Interpretability — 5 citations into it; #1,338 of 2,251 by trust here, #1,009 by citations

Whom Thomas Manzini trusts overall

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

1. Narissra Maria Punyanunt-Carter
2. Tomas Mikolov
3. Geoffrey E. Hinton
4. Hila Gonen
5. Beth G. Chung-Herrera
6. Diederik P. Kingma
7. Ilya Sutskever
8. Yoshua Bengio
9. Aylin Caliskan
10. Ella Rabinovich

Who trusts Thomas Manzini overall

1. Percy Liang
2. Sunipa Dev
3. Deven Santosh Shah
4. Nicholas Meade
5. Andrew Silva
6. Radovan Popović
7. Anne Lauscher
8. Malvina Nissim
9. Kawin Ethayarajh
10. Tony Sun

Papers from Thomas Manzini's perspective

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

Their papers

• Found in Translation: Learning Robust Joint Representations by Cyclic Translations Between Modalities (2018) — 560 citations
• Black is to Criminal as Caucasian is to Police: Detecting and Removing Multiclass Bias in Word Embeddings (2019) — 341 citations