Eric A. Wan
Artificial Intelligence · 1993–2009
A researcher in the Science corpus: 9 papers; trusts 52 researchers and is trusted by 78 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 31 citations into it; #3,467 of 35,345 by trust here, #6,569 by citations
- Probabilistic & Bayesian Methods — 21 citations into it; #725 of 1,525 by trust here, #581 by citations
- Aerospace Engineering — 18 citations into it; #684 of 6,421 by trust here, #1,602 by citations
- Electrical and Electronic Engineering — 13 citations into it; #9,753 of 16,539 by trust here, #15,621 by citations
- Signal Processing — 12 citations into it; #799 of 7,572 by trust here, #1,351 by citations
- Computer Networks and Communications — 8 citations into it; #6,790 of 9,886 by trust here, #9,214 by citations
- Computer Vision and Pattern Recognition — 6 citations into it
- Robotics & Control — 6 citations into it
Whom Eric A. Wan trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- David John Cameron MacKay
- Simon Justin Julier
- Rudolph van der Merwe
- A. Waibel
- Arthur P. Dempster
- Yann LeCun
- Jeffrey K. Uhlmann
- Simon S. Haykin
- Arnaud Doucet
- Yoshua Bengio
Who trusts Eric A. Wan overall
- Rudolph van der Merwe
- Anindya Sao Paul
- Jianye Ching
- Simo Särkkä
- John L. Crassidis
- Bryan Lim
- Piotr Wojciech Mirowski
- L. Bailey
- Luke Wallace
- Harri Valpola
Papers from Eric A. Wan's perspective
Ordered by how strongly the researchers Eric A. Wan 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)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- The unscented Kalman filter for nonlinear estimation (2000) — 4,471 citations
- The Unscented Kalman Filter (2002) — 560 citations
- RSSI-Based Indoor Localization and Tracking Using Sigma-Point Kalman Smoothers (2009) — 298 citations
- State-Dependent Riccati Equation Control for Small Autonomous Helicopters (2007) — 81 citations
- Sigma-Point Kalman Filters for Nonlinear Estimation and Sensor-Fusion: Applications to Integrated Navigation (2004) — 529 citations
- Sigma-point kalman filters for probabilistic inference in dynamic state-space models (2004) — 1,222 citations
- The square-root unscented Kalman filter for state and parameter-estimation (2001) — 1,225 citations
- The Unscented Particle Filter (2000) — 1,778 citations
- Time series prediction by using a connectionist network with internal delay lines (1993)