Marina Meil

Computational Theory and Mathematics · 2017

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

• Computational Theory and Mathematics — 7 citations into it
• Representation & Self-Supervised Learning — 5 citations into it

Whom Marina Meil trusts overall

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

1. John M. Lee
2. Amit Singer
3. Nakul Verma
4. Evarist Gin'e
5. Matthias Hein
6. Michele Ceriotti
7. I. Borg
8. Josh Tenenbaum
9. Stefan Chmiela
10. Vladimir Koltchinskii

Papers from Marina Meil's perspective

Ordered by how strongly the researchers Marina Meil trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Gradient-based learning applied to document recognition
3. ImageNet classification with deep convolutional neural networks
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. ImageNet: A large-scale hierarchical image database
6. Riemannian Manifolds: An Introduction to Curvature
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. Hessian eigenmaps: Locally linear embedding techniques for high-dimensional data
10. Long Short-Term Memory

Their papers

• Metric Learning and Manifolds: Preserving the Intrinsic Geometry (2017)