Ewan Dunbar
Artificial Intelligence · 2013–2021
A researcher in the Science corpus: 8 papers; trusts 76 researchers and is trusted by 15 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 139 citations into it; #10,481 of 35,345 by trust here, #6,378 by citations
- Natural Language Processing — 72 citations into it
- Speech & Audio — 72 citations into it; #451 of 1,076 by trust here, #336 by citations
- Signal Processing — 63 citations into it; #2,165 of 7,572 by trust here, #918 by citations
- Representation & Self-Supervised Learning — 45 citations into it; #2,958 of 3,145 by trust here, #3,047 by citations
- Computer Vision and Pattern Recognition — 36 citations into it
- Evaluation & Benchmarks — 25 citations into it
Whom Ewan Dunbar trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Maarten Versteegh
- Aren Jansen
- Geoffrey E. Hinton
- Thomas Schatz
- Diederik P. Kingma
- Yoshua Bengio
- Ilya Sutskever
- Yann LeCun
- Alex Krizhevsky
- Alex Graves
Who trusts Ewan Dunbar overall
- David F. Harwath
- Morgane Rivière
- Wei-Ning Hsu
- Emmanuel Dupoux
- Evgeny Kharitonov
- James R. Glass
- Thomas Schatz
- Tu Nguyen
- Herman Kamper
- Abdel-rahman Mohamed
Papers from Ewan Dunbar's perspective
Ordered by how strongly the researchers Ewan Dunbar trusts endorse each paper. Same corpus, a different order for every researcher.
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- 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)
- Long Short-Term Memory
- Gradient-based learning applied to document recognition
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
Their papers
- A summary of the 2012 JHU CLSP workshop on zero resource speech technologies and models of early language acquisition (2013) — 113 citations
- The Zero Resource Speech Challenge 2019: TTS without T (2019) — 129 citations
- A hybrid dynamic time warping-deep neural network architecture for unsupervised acoustic modeling (2015) — 75 citations
- The Zero Resource Speech Benchmark 2021: Metrics and baselines for unsupervised spoken language modeling (2020) — 135 citations
- The Zero Resource Speech Challenge 2020: Discovering discrete subword and word units (2020) — 66 citations
- RNNs Implicitly Implement Tensor Product Representations (2018) — 61 citations
- The Zero Resource Speech Challenge 2021: Spoken Language Modelling (2021) — 68 citations
- Learning Weakly Supervised Multimodal Phoneme Embeddings (2017) — 12 citations