Karl Mutch

Artificial Intelligence · 2010–2019

A researcher in the Science corpus: 2 papers; trusts 9 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 31 citations into it
• Natural Language Processing — 5 citations into it

Whom Karl Mutch trusts overall

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

1. Ronald J. Williams
2. Tomas Mikolov
3. Diederik P. Kingma
4. Faustino J. Gomez

Papers from Karl Mutch's perspective

Ordered by how strongly the researchers Karl Mutch 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Going deeper with convolutions
4. ImageNet classification with deep convolutional neural networks
5. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
8. Densely Connected Convolutional Networks
9. Attention is All you Need (Neural Information Processing Systems)
10. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning

Their papers

• Human Genome Sequencing Using Unchained Base Reads on Self-Assembling DNA Nanoarrays (2010) — 1,234 citations
• Evolutionary neural AutoML for deep learning (2019) — 120 citations