Alice Shoshana Jakobovits

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 24 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 17 citations into it; #28,960 of 35,345 by trust here, #28,481 by citations
• Information Systems — 15 citations into it; #6,709 of 8,771 by trust here, #6,770 by citations
• Natural Language Processing — 12 citations into it
• Software — 8 citations into it
• Code Generation & Program Synthesis — 7 citations into it; #165 of 220 by trust here, #190 by citations
• Hardware and Architecture — 6 citations into it
• Computer Networks and Communications — 5 citations into it
• Model Architectures — 5 citations into it

Whom Alice Shoshana Jakobovits trusts overall

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

1. Miltiadis Allamanis
2. Tomas Mikolov
3. Jeffrey L. Elman
4. Veselin Raychev
5. Sepp Hochreiter
6. Sergey Ioffe
7. Geoffrey E. Hinton
8. Ilya Sutskever
9. Yoshua Bengio
10. Alex Graves

Who trusts Alice Shoshana Jakobovits overall

1. Yichen Xu
2. Ruchi Puri
3. Zhan Shi
4. Paras Jain

Papers from Alice Shoshana Jakobovits's perspective

Ordered by how strongly the researchers Alice Shoshana Jakobovits trusts endorse each paper. Same corpus, a different order for every researcher.

1. Long Short-Term Memory
2. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)

Their papers

• Neural Code Comprehension: A Learnable Representation of Code Semantics (2018) — 276 citations
• CP2K: An electronic structure and molecular dynamics software package - Quickstep: Efficient and accurate electronic structure calculations. (2020) — 3,532 citations