Rudolph van der Merwe
Artificial Intelligence · 2000–2004
A researcher in the Science corpus: 6 papers; trusts 29 researchers and is trusted by 75 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 22 citations into it; #3,519 of 35,345 by trust here, #6,720 by citations
- Probabilistic & Bayesian Methods — 19 citations into it; #724 of 1,525 by trust here, #581 by citations
- Aerospace Engineering — 10 citations into it; #648 of 6,421 by trust here, #1,602 by citations
- Signal Processing — 10 citations into it; #782 of 7,572 by trust here, #1,351 by citations
- Robotics & Control — 6 citations into it
- Statistical and Nonlinear Physics — 5 citations into it; #1,741 of 10,127 by trust here, #4,439 by citations
- Statistics and Probability — 5 citations into it
Whom Rudolph van der Merwe trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Simon Justin Julier
- Eric A. Wan
- Simon S. Haykin
- Arnaud Doucet
- David John Cameron MacKay
- Yoshua Bengio
- Neil J. Gordon
- John F. Canny
- Vladislav Gavrilets
- Arthur P. Dempster
Who trusts Rudolph van der Merwe overall
- Eric A. Wan
- Simo Särkkä
- Anindya Sao Paul
- Jianye Ching
- John L. Crassidis
- S. Andrew Gadsden
- Julien Cornebise
- Arnaud Doucet
- Luke Wallace
- Stefano Mariani
Papers from Rudolph van der Merwe's perspective
Ordered by how strongly the researchers Rudolph van der Merwe trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- 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)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- The unscented Kalman filter for nonlinear estimation (2000) — 4,471 citations
- The Unscented Kalman Filter (2002) — 560 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