Lee A. Feldkamp

Model Architectures · 1994–2003

A researcher in the Science corpus: 5 papers; trusts 6 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Model Architectures — 11 citations into it
• Optimization & Training — 7 citations into it

Whom Lee A. Feldkamp trusts overall

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

1. Ronald J. Williams
2. Paul J. Werbos
3. Charles M. Bishop
4. G. Puskorius
5. Yoshua Bengio
6. Jing Peng
7. Patrice Y. Simard
8. Simon S. Haykin
9. Richard S. Sutton
10. Paolo Frasconi

Who trusts Lee A. Feldkamp overall

1. J. Urgen Schmidhuber
2. Laurence Aitchison
3. Danil V. Prokhorov
4. M. C. Ozturk
5. Yu Hen Hu
6. Sepp Hochreiter
7. J. J. Rubio
8. Paulin Coulibaly
9. Jun Li
10. Mantas Lukosevicius

Papers from Lee A. Feldkamp's perspective

Ordered by how strongly the researchers Lee A. Feldkamp 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. ImageNet Large Scale Visual Recognition Challenge
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Simple and conditioned adaptive behavior from Kalman filter trained recurrent networks (2003) — 67 citations
• Enhanced Multi-Stream Kalman Filter Training for Recurrent Networks (1998)
• Robust neural learning from unbalanced data samples (1998)
• A signal processing framework based on dynamic neural networks with application to problems in adaptation, filtering, and classification (1998)
• Neurocontrol of nonlinear dynamical systems with Kalman filter trained recurrent networks (1994)