Layla El Asri
Artificial Intelligence · 2016–2022
A researcher in the Science corpus: 8 papers; trusts 154 researchers and is trusted by 21 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 124 citations into it; #9,282 of 35,345 by trust here, #4,829 by citations
- Natural Language Processing — 88 citations into it; #2,229 of 5,688 by trust here, #1,540 by citations
- Reinforcement Learning — 55 citations into it; #1,925 of 2,242 by trust here, #1,028 by citations
- Computer Vision and Pattern Recognition — 47 citations into it; #14,380 of 21,575 by trust here, #10,334 by citations
- Model Architectures — 15 citations into it
- Evaluation & Benchmarks — 14 citations into it; #2,165 of 3,147 by trust here, #2,009 by citations
- Management Science and Operations Research — 7 citations into it
- Optimization & Training — 7 citations into it
Whom Layla El Asri trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Matthew Henderson
- Jason Williams
- Diederik P. Kingma
- Yoshua Bengio
- Geoffrey E. Hinton
- Richard S. Sutton
- Ronald J. Williams
- Ilya Sutskever
- Alex Krizhevsky
- Robert Tibshirani
Who trusts Layla El Asri overall
- Paweł Budzianowski
- Prithviraj Ammanabrolu
- Zachary Chase Lipton
- Baolin Peng
- Jianfeng Gao
- Shrimai Prabhumoye
- Yutong Shao
- Pararth Shah
- Milan Gritta
- Daniel S. Brown
Papers from Layla El Asri's perspective
Ordered by how strongly the researchers Layla El Asri trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
Their papers
- TextWorld: A Learning Environment for Text-based Games (2018) — 482 citations
- Frames: a corpus for adding memory to goal-oriented dialogue systems (2017) — 280 citations
- Policy Networks with Two-Stage Training for Dialogue Systems (2016) — 110 citations
- Relevance of Unsupervised Metrics in Task-Oriented Dialogue for Evaluating Natural Language Generation (2017) — 232 citations
- Towards Solving Text-based Games by Producing Adaptive Action Spaces (2018) — 14 citations
- Why Exposure Bias Matters: An Imitation Learning Perspective of Error Accumulation in Language Generation (2022) — 131 citations
- Tell, Draw, and Repeat: Generating and Modifying Images Based on Continual Linguistic Instruction (2018) — 129 citations
- Score-based Inverse Reinforcement Learning (2016) — 41 citations