Jonathon A. Chambers

Artificial Intelligence · 2001–2019

A researcher in the Science corpus: 7 papers; trusts 22 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it; #12,473 of 35,345 by trust here, #17,776 by citations
• Computer Vision and Pattern Recognition — 17 citations into it
• Model Architectures — 14 citations into it
• Computer Networks and Communications — 6 citations into it; #5,646 of 9,886 by trust here, #8,844 by citations
• Statistical Learning Theory — 6 citations into it
• Optimization & Training — 5 citations into it
• Scaling & Learning Theory — 5 citations into it

Whom Jonathon A. Chambers trusts overall

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

1. Paul J. Werbos
2. Kenneth M. Rose
3. Yoshua Bengio
4. Tomaso A. Poggio
5. A. Robinson
6. George M. Georgiou
7. Radford M. Neal
8. Ronald J. Williams
9. Alex Krizhevsky
10. Geoffrey E. Hinton

Who trusts Jonathon A. Chambers overall

1. Ruiyang Zhang
2. Petr Kadlec
3. Yisi Liu
4. Haiping Lu
5. Yang Liu
6. Kamran Kowsari
7. Ankit Thakkar

Papers from Jonathon A. Chambers's perspective

Ordered by how strongly the researchers Jonathon A. Chambers 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• A Posture Recognition-Based Fall Detection System for Monitoring an Elderly Person in a Smart Home Environment (2012) — 322 citations
• Deep Learning Models for Cyber Security in IoT Networks (2019) — 318 citations
• A Novel Adaptive Kalman Filter With Inaccurate Process and Measurement Noise Covariance Matrices (2018) — 626 citations
• A Novel Robust Student's t-Based Kalman Filter (2017) — 454 citations
• Deep learning for posture analysis in fall detection (2014) — 58 citations
• EEG Signal Processing (2007) — 1,718 citations
• Recurrent Neural Networks for Prediction: Learning Algorithms, Architectures and Stability (2001) — 630 citations