Heinrich Müller
Computer Vision and Pattern Recognition · 2017
A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 8 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 13 citations into it; #9,211 of 21,575 by trust here, #10,154 by citations
- Graph Learning — 12 citations into it; #307 of 693 by trust here, #366 by citations
- Computational Mechanics — 11 citations into it
- Artificial Intelligence — 9 citations into it; #14,194 of 35,345 by trust here, #15,004 by citations
Whom Heinrich Müller trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
Who trusts Heinrich Müller overall
Papers from Heinrich Müller's perspective
Ordered by how strongly the researchers Heinrich Müller trusts endorse each paper. Same corpus, a different order for every researcher.
- Gradient-based learning applied to document recognition
- GradientBased Learning Applied to Document Recognition
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Spectral Networks and Locally Connected Networks on Graphs
- Attention is All you Need (Neural Information Processing Systems)
- Going deeper with convolutions
Their papers
- SplineCNN: Fast Geometric Deep Learning with Continuous B-Spline Kernels (2017) — 511 citations