Ehsan Hosseini-Asl
Artificial Intelligence · 2016–2021
A researcher in the Science corpus: 5 papers; trusts 159 researchers and is trusted by 33 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 120 citations into it; #6,652 of 35,345 by trust here, #8,619 by citations
- Natural Language Processing — 85 citations into it; #2,017 of 5,688 by trust here, #2,808 by citations
- Computer Vision and Pattern Recognition — 41 citations into it; #17,785 of 21,575 by trust here, #16,787 by citations
- Model Architectures — 13 citations into it
- Representation & Self-Supervised Learning — 13 citations into it; #3,091 of 3,145 by trust here, #1,811 by citations
- Optimization & Training — 10 citations into it
- Psychiatry and Mental health — 8 citations into it
- Generative Models — 5 citations into it
Whom Ehsan Hosseini-Asl trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yoshua Bengio
- Geoffrey E. Hinton
- Diederik P. Kingma
- Ilya Sutskever
- Alex Krizhevsky
- Yann LeCun
- Jimmy Ba
- Richard Socher
- Matthew D. Zeiler
- Kaiming He
Who trusts Ehsan Hosseini-Asl overall
- Andrea Madotto
- Zhaojiang Lin
- Genta Indra Winata
- Jyoti Islam
- Chia-Hsuan Lee
- Li Zhou
- Manhua Liu
- Jinjie Ni
- Chenguang Wang
- Biswesh Mohapatra
Papers from Ehsan Hosseini-Asl's perspective
Ordered by how strongly the researchers Ehsan Hosseini-Asl trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- A Simple Language Model for Task-Oriented Dialogue (2020) — 583 citations
- Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems (2019) — 481 citations
- Toward Scalable Neural Dialogue State Tracking Model (2018) — 84 citations
- Alzheimer's disease diagnostics by adaptation of 3D convolutional network (2016) — 314 citations
- Joint Energy-based Model Training for Better Calibrated Natural Language Understanding Models (2021) — 24 citations