Asif Ekbal
Artificial Intelligence · 2015–2021
A researcher in the Science corpus: 5 papers; trusts 32 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 48 citations into it
- Natural Language Processing — 35 citations into it
- Evaluation & Benchmarks — 19 citations into it
- Computer Vision and Pattern Recognition — 10 citations into it
- Model Architectures — 6 citations into it
Whom Asif Ekbal trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
- Ilya Sutskever
- Alex Krizhevsky
- Kyunghyun Cho
- Yoon Kim
- Tomas Mikolov
- Nitish Srivastava
- Ruslan Salakhutdinov
Papers from Asif Ekbal's perspective
Ordered by how strongly the researchers Asif Ekbal trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- 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)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
Their papers
- MMQA: A Multi-domain Multi-lingual Question-Answering Framework for English and Hindi (2018) — 59 citations
- COVIDRead: A Large-scale Question Answering Dataset on COVID-19 (2021) — 6 citations
- The CHEMDNER corpus of chemicals and drugs and its annotation principles (2015) — 444 citations
- A Multilayer Perceptron based Ensemble Technique for Fine-grained Financial Sentiment Analysis (2017) — 94 citations
- Fighting an Infodemic: COVID-19 Fake News Dataset (2020) — 368 citations