Lukas Drude
Artificial Intelligence · 2016–2020
A researcher in the Science corpus: 7 papers; trusts 34 researchers and is trusted by 20 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 58 citations into it
- Signal Processing — 57 citations into it; #1,441 of 7,572 by trust here, #1,560 by citations
- Speech & Audio — 38 citations into it; #719 of 1,076 by trust here, #628 by citations
- Computer Vision and Pattern Recognition — 13 citations into it
- Computational Mechanics — 11 citations into it; #3,073 of 10,001 by trust here, #3,190 by citations
- Model Architectures — 10 citations into it
- Optimization & Training — 10 citations into it
- Evaluation & Benchmarks — 8 citations into it
Whom Lukas Drude trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Takuya Yoshioka
- Geoffrey E. Hinton
- Tomohiro Nakatani
- Paul J. Werbos
- Shinji Watanabe
- Ilya Sutskever
- Emmanuel Vincent
- Keisuke Kinoshita
- Alex Krizhevsky
- Sergey Ioffe
Who trusts Lukas Drude overall
- Shinji Watanabe
- Jinyu Li
- Kateřina Žmolíková
- Yusuke Fujita
- Christoph Boeddeker
- Shota Horiguchi
- Tae Jin Park
- Zhuo Chen
- Marc Delcroix
- Ivan Medennikov
Papers from Lukas Drude's perspective
Ordered by how strongly the researchers Lukas Drude trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
- ImageNet: A large-scale hierarchical image database
- Going deeper with convolutions
Their papers
- Hidden Markov Model Variational Autoencoder for Acoustic Unit Discovery (2017) — 47 citations
- Multi-talker ASR for an unknown number of sources: Joint training of source counting, separation and ASR (2020) — 46 citations
- Front-end processing for the CHiME-5 dinner party scenario (2018) — 146 citations
- Listening to Each Speaker One by One with Recurrent Selective Hearing Networks (2018) — 82 citations
- NARA-WPE: A Python package for weighted prediction error dereverberation in Numpy and Tensorflow for online and offline processing (2018) — 134 citations
- Neural network based spectral mask estimation for acoustic beamforming (2016) — 514 citations
- The RWTH/UPB/FORTH System Combination for the 4th CHiME Challenge Evaluation (2016) — 48 citations