Brian M. Sadler

Artificial Intelligence · 2000–2022

A researcher in the Science corpus: 11 papers; trusts 69 researchers and is trusted by 54 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 66 citations into it; #9,536 of 35,345 by trust here, #13,962 by citations
• Computer Networks and Communications — 43 citations into it; #908 of 9,886 by trust here, #1,322 by citations
• Computer Vision and Pattern Recognition — 37 citations into it
• Natural Language Processing — 37 citations into it
• Electrical and Electronic Engineering — 27 citations into it; #1,669 of 16,539 by trust here, #5,871 by citations
• Computational Mechanics — 10 citations into it
• Reinforcement Learning — 10 citations into it
• Optimization & Training — 7 citations into it

Whom Brian M. Sadler trusts overall

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

1. Qing Zhao
2. Shridhar Mubaraq Mishra
3. Ananthram Swami
4. Angelia Nedić
5. Lang Tong
6. Yunxia Chen
7. John N. Tsitsiklis
8. Geoffrey E. Hinton
9. Dimitri P. Bertsekas
10. Yoshua Bengio

Who trusts Brian M. Sadler overall

1. Qing Zhao
2. Amrit Singh Bedi
3. Tevfik Yücek
4. Octavia A. Dobre
5. Ying-Chang Liang
6. Keqin Liu
7. Zabih Ghassemlooy
8. Muhammad Waqar Aslam
9. Jefferson L. Xu
10. Fahed Hameed

Papers from Brian M. Sadler's perspective

Ordered by how strongly the researchers Brian M. Sadler 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• LLM-Planner: Few-Shot Grounded Planning for Embodied Agents with Large Language Models (2022) — 743 citations
• Beyond I.I.D.: Three Levels of Generalization for Question Answering on Knowledge Bases (2020) — 329 citations
• A Survey of Dynamic Spectrum Access (2007) — 2,823 citations
• Modeling of non-line-of-sight ultraviolet scattering channels for communication (2009) — 314 citations
• Ultraviolet Communications: Potential and State-Of-The-Art (2008) — 502 citations
• Hierarchical digital modulation classification using cumulants (2000) — 1,098 citations
• Proximity Without Consensus in Online Multiagent Optimization (2016) — 90 citations
• Opportunistic Spectrum Access via Periodic Channel Sensing (2008) — 388 citations
• COGNITIVE RADIOS FOR DYNAMIC SPECTRUM ACCESS - Dynamic Spectrum Access in the Time Domain: Modeling and Exploiting White Space (2007) — 563 citations
• A Survey of Time Delay Estimation Performance Bounds (2006) — 71 citations
• Dynamic Spectrum Access: Signal Processing, Networking, and Regulatory Policy (2006) — 401 citations