Abbas Khosravi

Artificial Intelligence · 2011–2023

A researcher in the Science corpus: 8 papers; trusts 83 researchers and is trusted by 20 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 215 citations into it; #12,466 of 35,345 by trust here, #10,065 by citations
• Computer Vision and Pattern Recognition — 115 citations into it
• Probabilistic & Bayesian Methods — 56 citations into it
• Reinforcement Learning — 42 citations into it
• Control and Systems Engineering — 32 citations into it
• Electrical and Electronic Engineering — 28 citations into it; #3,156 of 16,539 by trust here, #5,738 by citations
• Management Science and Operations Research — 27 citations into it; #6,091 of 11,946 by trust here, #5,548 by citations
• Model Architectures — 21 citations into it

Whom Abbas Khosravi trusts overall

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

1. David John Cameron MacKay
2. Tom M. Heskes
3. Charles M. Bishop
4. David E. Goldberg
5. Geoffrey E. Hinton
6. Alex Krizhevsky
7. Sergey Levine
8. Diederik P. Kingma
9. Pieter Abbeel
10. Radford M. Neal

Who trusts Abbas Khosravi overall

1. Hao Quan
2. Tim Pearce
3. Dipti Srinivasan
4. Dawn An
5. Alexandra Melike Brintrup
6. Grzegorz Dudek
7. Elia Kaufmann
8. Muhammad Naveed Akhter
9. Murat Kuzlu
10. Mohamed H. Zaki

Papers from Abbas Khosravi's perspective

Ordered by how strongly the researchers Abbas Khosravi trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• A review on artificial intelligence based load demand forecasting techniques for smart grid and buildings (2015) — 924 citations
• Short-Term Load and Wind Power Forecasting Using Neural Network-Based Prediction Intervals (2014) — 571 citations
• Comprehensive Review of Neural Network-Based Prediction Intervals and New Advances (2011) — 640 citations
• Lower Upper Bound Estimation Method for Construction of Neural Network-Based Prediction Intervals (2011) — 707 citations
• A Survey of Imitation Learning: Algorithms, Recent Developments, and Challenges (2023) — 329 citations
• Epileptic Seizures Detection Using Deep Learning Techniques: A Review (2020) — 385 citations
• A Review of Uncertainty Quantification in Deep Learning: Techniques, Applications and Challenges (2020) — 2,678 citations
• Extreme learning machine based transfer learning algorithms: A survey (2017) — 79 citations