Robert R. Richardson
Automotive Engineering · 2014–2017
A researcher in the Science corpus: 3 papers; trusts 11 researchers and is trusted by 7 researchers here, as inferred from the citation graph.
Subfields
- Automotive Engineering — 37 citations into it; #779 of 3,081 by trust here, #913 by citations
- Electrical and Electronic Engineering — 32 citations into it; #5,166 of 16,539 by trust here, #5,257 by citations
- Control and Systems Engineering — 13 citations into it
- Artificial Intelligence — 12 citations into it
- Probabilistic & Bayesian Methods — 7 citations into it
- Safety, Risk, Reliability and Quality — 5 citations into it
Whom Robert R. Richardson trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Carl E. Rasmussen
- Michael A. Osborne
- Kevin P. Murphy
- Caihao Weng
- Hannes Nickisch
- Maitane Berecibar
- Matthieu Dubarry
- Dong Wang
- Christoph R. Birkl
- Wei He
Who trusts Robert R. Richardson overall
- Kailong Liu
- Xiaosong Hu
- S. Alavi
- Fujin Wang
- Yi Li
- D. Roman
- Satadru Dey
- Valentin Sulzer
- Weihan Li
- Christoph R. Birkl
Papers from Robert R. Richardson's perspective
Ordered by how strongly the researchers Robert R. Richardson 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
- Learning Multiple Layers of Features from Tiny Images
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- 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)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
Their papers
- Gaussian Process Regression for In Situ Capacity Estimation of Lithium-Ion Batteries (2017) — 315 citations
- Gaussian process regression for forecasting battery state of health (2017) — 627 citations
- Battery internal temperature estimation by combined impedance and surface temperature measurement (2014) — 257 citations