Jesper Højvang Jensen

Signal Processing · 2010–2020

A researcher in the Science corpus: 6 papers; trusts 90 researchers and is trusted by 102 researchers here, as inferred from the citation graph.

Subfields

• Signal Processing — 113 citations into it; #208 of 7,572 by trust here, #309 by citations
• Artificial Intelligence — 68 citations into it; #3,648 of 35,345 by trust here, #6,378 by citations
• Speech & Audio — 43 citations into it; #90 of 1,076 by trust here, #170 by citations
• Computer Vision and Pattern Recognition — 36 citations into it
• Cognitive Neuroscience — 31 citations into it; #836 of 10,852 by trust here, #1,743 by citations
• Computational Mechanics — 25 citations into it; #1,748 of 10,001 by trust here, #1,651 by citations
• Model Architectures — 22 citations into it
• Natural Language Processing — 20 citations into it

Whom Jesper Højvang Jensen trusts overall

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

1. Martin P. Cooke
2. Carla Lopes
3. Cees H. Taal
4. Geoffrey E. Hinton
5. Dong Yu
6. Yoshua Bengio
7. Yann LeCun
8. P. Loizou
9. Michael I. Jordanzoubin
10. Yuxuan Wang

Who trusts Jesper Højvang Jensen overall

1. Yi Luo
2. Deliang Wang
3. Daniel Michelsanti
4. Zhuo Chen
5. Prajwal K R
6. Alexander H. Liu
7. Jonathan Le Roux
8. Jacob Donley
9. Yuma Koizumi
10. Ruohan Gao

Papers from Jesper Højvang Jensen's perspective

Ordered by how strongly the researchers Jesper Højvang Jensen 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. Long Short-Term Memory
4. ImageNet classification with deep convolutional neural networks
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. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
10. ImageNet: A large-scale hierarchical image database

Their papers

• Multitalker Speech Separation With Utterance-Level Permutation Invariant Training of Deep Recurrent Neural Networks (2017) — 782 citations
• Permutation invariant training of deep models for speaker-independent multi-talker speech separation (2016) — 961 citations
• A short-time objective intelligibility measure for time-frequency weighted noisy speech (2010) — 1,274 citations
• An Algorithm for Predicting the Intelligibility of Speech Masked by Modulated Noise Maskers (2016) — 729 citations
• An Overview of Deep-Learning-Based Audio-Visual Speech Enhancement and Separation (2020) — 337 citations
• An Algorithm for Intelligibility Prediction of Time–Frequency Weighted Noisy Speech (2011) — 2,397 citations