Maria Stokes

Probabilistic & Bayesian Methods · 2004

A researcher in the Science corpus: 1 paper; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Probabilistic & Bayesian Methods — 6 citations into it

Whom Maria Stokes trusts overall

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

1. Michael I. Jordan
2. Zoubin Ghahramani
3. James O. Berger
4. Yann LeCun
5. Carl Dean Meyer
6. Tommi S. Jaakkola
7. Jonathan R. Wolpaw
8. Neil J. Gordon
9. Yoshua Bengio
10. Harri Valpola

Papers from Maria Stokes's perspective

Ordered by how strongly the researchers Maria Stokes 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. Learning Multiple Layers of Features from Tiny Images
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Adaptive BCI based on variational Bayesian Kalman filtering: an empirical evaluation (2004) — 108 citations