M. Heinonen

Artificial Intelligence · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 13 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it; #20,730 of 35,345 by trust here, #29,412 by citations
• Probabilistic & Bayesian Methods — 17 citations into it; #1,081 of 1,525 by trust here, #1,313 by citations
• Computer Vision and Pattern Recognition — 12 citations into it; #12,922 of 21,575 by trust here, #18,782 by citations

Whom M. Heinonen trusts overall

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

1. Stéphane Mallat
2. Alex Krizhevsky
3. James Hensman
4. Mark van der Wilk
5. Leland McInnes
6. Alexander G. de G. Matthews
7. Hugh Salimbeni
8. Zoubin Ghahramani
9. Andrew Gordon Wilson

Who trusts M. Heinonen overall

1. Greg Yang
2. Leland McInnes

Papers from M. Heinonen's perspective

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

1. Learning Multiple Layers of Features from Tiny Images
2. ImageNet classification with deep convolutional neural networks
3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Long Short-Term Memory
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning

Their papers

• Deep convolutional Gaussian processes (2018) — 65 citations
• Flex ddG: Rosetta Ensemble-Based Estimation of Changes in Protein-Protein Binding Affinity Upon Mutation (2017) — 274 citations