Agnieszka Grabska-Barwinska

Artificial Intelligence · 2016–2021

A researcher in the Science corpus: 7 papers; trusts 23 researchers and is trusted by 172 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 105 citations into it; #1,809 of 35,345 by trust here, #339 by citations
• Computer Vision and Pattern Recognition — 46 citations into it
• Reinforcement Learning — 35 citations into it
• Meta & Continual Learning — 10 citations into it

Whom Agnieszka Grabska-Barwinska trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Alex Graves
4. Richard S. Sutton
5. Yann LeCun
6. J. Urgen Schmidhuber
7. Diederik P. Kingma
8. Alex Krizhevsky
9. Ronald J. Williams
10. Ilya Sutskever

Who trusts Agnieszka Grabska-Barwinska overall

1. Gyuhak Kim
2. Jorge Armando Mendez Mendez
3. Liyuan Wang
4. Vincenzo Lomonaco
5. Timothée Lesort
6. Frederik Benzing
7. Gido M. van de Ven
8. Matteo Boschini
9. Rahaf Aljundi
10. Oleksiy Ostapenko

Papers from Agnieszka Grabska-Barwinska's perspective

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

Their papers

• Overcoming catastrophic forgetting in neural networks (2016) — 10,384 citations
• Hybrid computing using a neural network with dynamic external memory (2016) — 1,765 citations
• Progress & Compress: A scalable framework for continual learning (2018) — 1,048 citations
• Unsupervised Predictive Memory in a Goal-Directed Agent (2018) — 206 citations
• Online Learning with Gated Linear Networks (2017) — 26 citations
• Effective gene expression prediction from sequence by integrating long-range interactions (2021) — 1,222 citations
• Unveiling the predictive power of static structure in glassy systems (2020) — 349 citations