Lauri Juvela
Artificial Intelligence · 2017–2020
A researcher in the Science corpus: 9 papers; trusts 155 researchers and is trusted by 27 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 120 citations into it; #5,896 of 35,345 by trust here, #8,077 by citations
- Speech & Audio — 94 citations into it
- Signal Processing — 92 citations into it; #875 of 7,572 by trust here, #933 by citations
- Generative Models — 51 citations into it
- Natural Language Processing — 49 citations into it; #3,547 of 5,688 by trust here, #4,682 by citations
- Computer Vision and Pattern Recognition — 46 citations into it
- Optimization & Training — 12 citations into it
- Model Architectures — 11 citations into it
Whom Lauri Juvela trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Aäron van den Oord
- Heiga Zen
- Geoffrey E. Hinton
- Jimmy Ba
- John I. Makhoul
- Yoshua Bengio
- Kaiming He
- Alex Graves
- Karen Simonyan
Who trusts Lauri Juvela overall
- Bajibabu Bollepalli
- Junichi Yamagishi
- Eunwoo Song
- Yang Cui
- Ryuichi Yamamoto
- Xin Eric Wang
- Qiao Tian
- Yang Ai
- Xu Tan
- Jean-Marc Valin
Papers from Lauri Juvela's perspective
Ordered by how strongly the researchers Lauri Juvela 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
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- GlotNet—A Raw Waveform Model for the Glottal Excitation in Statistical Parametric Speech Synthesis (2019) — 44 citations
- Non-parallel voice conversion using i-vector PLDA: towards unifying speaker verification and transformation (2017) — 72 citations
- Conditional Spoken Digit Generation with StyleGAN (2020) — 11 citations
- ASVspoof 2019: A large-scale public database of synthesized, converted and replayed speech (2019) — 651 citations
- GELP: GAN-Excited Liner Prediction for Speech Synthesis from Mel-spectrogram (2019) — 18 citations
- GELP: GAN-Excited Linear Prediction for Speech Synthesis from Mel-spectrogram (2019) — 26 citations
- A Comparison of Recent Waveform Generation and Acoustic Modeling Methods for Neural-Network-Based Speech Synthesis (2018) — 69 citations
- Speaker-independent raw waveform model for glottal excitation (2018) — 39 citations
- Generative Adversarial Network-Based Glottal Waveform Model for Statistical Parametric Speech Synthesis (2017) — 50 citations