Merlijn Blaauw
Artificial Intelligence · 2016–2019
A researcher in the Science corpus: 3 papers; trusts 188 researchers and is trusted by 15 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 34 citations into it
- Computer Vision and Pattern Recognition — 29 citations into it; #8,500 of 21,575 by trust here, #17,258 by citations
- Generative Models — 28 citations into it; #807 of 1,956 by trust here, #1,715 by citations
- Signal Processing — 23 citations into it; #1,955 of 7,572 by trust here, #4,560 by citations
- Speech & Audio — 17 citations into it
- Natural Language Processing — 7 citations into it
- Model Architectures — 6 citations into it
- Optimization & Training — 6 citations into it
Whom Merlijn Blaauw trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Geoffrey E. Hinton
- Yoshua Bengio
- Aäron van den Oord
- Kaiming He
- Danilo Jimenez Rezende
- Alex Graves
- Alex Krizhevsky
- Sergey Ioffe
- Yann LeCun
Who trusts Merlijn Blaauw overall
- Eliya Nachmani
- Adam Polyak
- Lior Wolf
- Wei-Ning Hsu
- Takuma Okamoto
- Pritish Chandna
- Jinglin Liu
- Lauri Juvela
- Laurent Girin
- Bo Liu
Papers from Merlijn Blaauw's perspective
Ordered by how strongly the researchers Merlijn Blaauw 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)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Learning Multiple Layers of Features from Tiny Images
Their papers
- A Neural Parametric Singing Synthesizer (2017) — 99 citations
- WGANSing: A Multi-Voice Singing Voice Synthesizer Based on the Wasserstein-GAN (2019) — 68 citations
- Modeling and Transforming Speech Using Variational Autoencoders (2016)