Moloud Abdar
Artificial Intelligence · 2019–2021
A researcher in the Science corpus: 4 papers; trusts 221 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 227 citations into it
- Computer Vision and Pattern Recognition — 149 citations into it
- Probabilistic & Bayesian Methods — 55 citations into it
Whom Moloud Abdar trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Geoffrey E. Hinton
- Diederik P. Kingma
- Alex Krizhevsky
- Radford M. Neal
- Yoshua Bengio
- Kaiming He
- Yann LeCun
- Ilya Sutskever
- Ruslan Salakhutdinov
- Karen Simonyan
Who trusts Moloud Abdar overall
Papers from Moloud Abdar's perspective
Ordered by how strongly the researchers Moloud Abdar 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)
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- ImageNet Large Scale Visual Recognition Challenge
- Learning Multiple Layers of Features from Tiny Images
Their papers
- A Review of Generalized Zero-Shot Learning Methods (2020) — 575 citations
- ABCDM: An Attention-based Bidirectional CNN-RNN Deep Model for sentiment analysis (2021) — 676 citations
- A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges (2020) — 2,678 citations
- A new machine learning technique for an accurate diagnosis of coronary artery disease (2019) — 299 citations