Janne Pylkkönen

Artificial Intelligence · 2016

A researcher in the Science corpus: 1 paper; trusts 12 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 8 citations into it
• Signal Processing — 5 citations into it

Whom Janne Pylkkönen trusts overall

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

1. Dong Yu
2. Andreas Stolcke
3. Geoffrey E. Hinton
4. Reinhard Kneser
5. Li Deng
6. Vimal Manohar
7. Sheng-Jun Huang
8. Yan Huang
9. Olga Kapralova
10. Daniel Povey

Papers from Janne Pylkkönen's perspective

Ordered by how strongly the researchers Janne Pylkkönen 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. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Active and Semi-Supervised Learning in ASR: Benefits on the Acoustic and Language Models (2016) — 66 citations