Eric Fosler-Lussier

Artificial Intelligence · 2002–2021

A researcher in the Science corpus: 8 papers; trusts 44 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 55 citations into it; #8,787 of 35,345 by trust here, #12,387 by citations
• Signal Processing — 21 citations into it; #1,502 of 7,572 by trust here, #2,911 by citations
• Molecular Biology — 19 citations into it
• Speech & Audio — 15 citations into it
• Natural Language Processing — 13 citations into it
• Model Architectures — 8 citations into it
• Computer Vision and Pattern Recognition — 6 citations into it
• Optimization & Training — 5 citations into it

Whom Eric Fosler-Lussier trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Brian Kingsbury
2. Ilya Sutskever
3. Geoffrey E. Hinton
4. Diederik P. Kingma
5. Michael I. Jordanzoubin
6. John D. Lafferty
7. Fei Sha
8. Kai-Fu Lee
9. Yoshua Bengio
10. Anthony J. Robinson

Who trusts Eric Fosler-Lussier overall

1. Li Deng
2. Dong Yu
3. Rohit Prabhavalkar
4. Mengqiu Wang
5. Ossama Abdel-Hamid
6. Geoffrey E. Hinton
7. Christopher D. Manning
8. Arash Vahdat
9. Abdel-rahman Mohamed
10. George E. Dahl

Papers from Eric Fosler-Lussier's perspective

Ordered by how strongly the researchers Eric Fosler-Lussier trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Attention is All you Need (Neural Information Processing Systems)
4. ImageNet classification with deep convolutional neural networks
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Backpropagation training for multilayer conditional random field based phone recognition (2010) — 43 citations
• Connectionist speech recognition of Broadcast News (2002) — 67 citations
• Discriminative Input Stream Combination for Conditional Random Field Phone Recognition (2009) — 10 citations
• Deep neural network based spectral feature mapping for robust speech recognition (2015) — 66 citations
• How essential are unstructured clinical narratives and information fusion to clinical trial recruitment? (2014) — 54 citations
• Hallucination of Speech Recognition Errors With Sequence to Sequence Learning (2021) — 24 citations
• A review of approaches to identifying patient phenotype cohorts using electronic health records (2013) — 528 citations
• Discourse Segmentation of Multi-Party Conversation (2003) — 422 citations