Manoochehr Ghiassi

Artificial Intelligence · 2005–2013

A researcher in the Science corpus: 2 papers; trusts 27 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 20 citations into it; #11,595 of 35,345 by trust here, #18,186 by citations
• Information Systems — 6 citations into it
• Economics and Econometrics — 5 citations into it
• Management Science and Operations Research — 5 citations into it; #5,816 of 11,946 by trust here, #6,563 by citations
• Model Architectures — 5 citations into it
• Statistics and Probability — 5 citations into it

Whom Manoochehr Ghiassi trusts overall

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

1. Peter D. Turney
2. Johan Bollen
3. Jeffrey L. Elman
4. Robert A. Jacobs
5. Michael Gamon
6. Alec Go
7. Adam Bermingham
8. Soo-Min Kim
9. Yiming Yang
10. Alexander Pak

Who trusts Manoochehr Ghiassi overall

1. B. Shravan Kumar
2. Vadlamani Ravi
3. Kumar Ravi
4. Anastasia Giahanou
5. Malika Aubakirova
6. Valentin Flunkert
7. Andrew Cook
8. Wafa S. Alorainy
9. Jie Wang
10. Mohit Bansal

Papers from Manoochehr Ghiassi's perspective

Ordered by how strongly the researchers Manoochehr Ghiassi 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. Long Short-Term Memory
4. Attention is All you Need (Neural Information Processing Systems)
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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. Thumbs up? Sentiment Classification using Machine Learning Techniques

Their papers

• A dynamic artificial neural network model for forecasting time series events (2005) — 272 citations
• Twitter brand sentiment analysis: A hybrid system using n-gram analysis and dynamic artificial neural network (2013) — 501 citations