Jan "Yenda" Trmal
Artificial Intelligence · 2014–2021
A researcher in the Science corpus: 7 papers; trusts 46 researchers and is trusted by 20 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 87 citations into it; #7,994 of 35,345 by trust here, #5,252 by citations
- Signal Processing — 67 citations into it; #1,277 of 7,572 by trust here, #514 by citations
- Speech & Audio — 67 citations into it; #376 of 1,076 by trust here, #262 by citations
- Computer Vision and Pattern Recognition — 24 citations into it
- Model Architectures — 17 citations into it; #970 of 2,278 by trust here, #1,433 by citations
- Natural Language Processing — 17 citations into it
- Computational Mechanics — 9 citations into it
Whom Jan "Yenda" Trmal trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Daniel Povey
- Geoffrey E. Hinton
- Yoshua Bengio
- Yann LeCun
- Mirco Ravanelli
- Alex Krizhevsky
- George E. Dahl
- Diederik P. Kingma
- Koray Kavukcuoglu
- Dong Yu
Who trusts Jan "Yenda" Trmal overall
- Daniel Povey
- Vimal Manohar
- László Tóth
- Vijayaditya Peddinti
- Sanjeev Khudanpur
- Shinji Watanabe
- John R. Hershey
- Kai Chen
- Daniel Garcia-Romero
- Adam Polyak
Papers from Jan "Yenda" Trmal's perspective
Ordered by how strongly the researchers Jan "Yenda" Trmal trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- Improving deep neural network acoustic models using generalized maxout networks (2014) — 315 citations
- GigaSpeech: An Evolving, Multi-domain ASR Corpus with 10, 000 Hours of Transcribed Audio (2021) — 607 citations
- Multi-Task Self-Supervised Learning for Robust Speech Recognition (2020) — 310 citations
- A pitch extraction algorithm tuned for automatic speech recognition (2014) — 350 citations
- The fifth 'CHiME' Speech Separation and Recognition Challenge: Dataset, task and baselines (2018) — 729 citations
- Lhotse: a speech data representation library for the modern deep learning ecosystem (2021) — 50 citations
- DiPCo - Dinner Party Corpus (2019) — 72 citations