Timothy Miller
Artificial Intelligence · 2011–2020
A researcher in the Science corpus: 11 papers; trusts 94 researchers and is trusted by 25 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 77 citations into it; #9,143 of 35,345 by trust here, #10,319 by citations
- Natural Language Processing — 34 citations into it; #4,696 of 5,688 by trust here, #5,593 by citations
- Molecular Biology — 21 citations into it; #11,871 of 17,773 by trust here, #13,009 by citations
- Computer Vision and Pattern Recognition — 15 citations into it
- Health Information Management — 14 citations into it
- Representation & Self-Supervised Learning — 14 citations into it
- Federated & Distributed Learning — 12 citations into it
- Evaluation & Benchmarks — 10 citations into it
Whom Timothy Miller trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Vincent Ng
- Diederik P. Kingma
- Radford M. Neal
- Geoffrey E. Hinton
- Yoshua Bengio
- Jakub Konecný
- Yann LeCun
- Ilya Sutskever
- Alex Krizhevsky
- H. Brendan McMahan
Who trusts Timothy Miller overall
- Yang Trista Cao
- Dinh C. Nguyen
- Rodolfo Stoffel Antunes
- Li Huang
- Hal Daumé Iii
- Dianbo Liu
- Dmitriy Dligach
- Anupam Guha
- Quoc-Viet Pham
- Li Li
Papers from Timothy Miller's perspective
Ordered by how strongly the researchers Timothy Miller trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- Long Short-Term Memory
- 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)
- Learning Multiple Layers of Features from Tiny Images
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- Federated pretraining and fine tuning of BERT using clinical notes from multiple silos (2020) — 38 citations
- Neural Temporal Relation Extraction (2017) — 96 citations
- Representations of Time Expressions for Temporal Relation Extraction with Convolutional Neural Networks (2017) — 39 citations
- A system for coreference resolution for the clinical narrative (2012) — 41 citations
- Two-stage Federated Phenotyping and Patient Representation Learning (2019) — 92 citations
- Automatic identification of methotrexate-induced liver toxicity in patients with rheumatoid arthritis from the electronic medical record (2015) — 73 citations
- Confederated Machine Learning on Horizontally and Vertically Separated Medical Data for Large-Scale Health System Intelligence (2019) — 10 citations
- XAI—Explainable artificial intelligence (2019) — 1,734 citations
- FADL: Federated-Autonomous Deep Learning for Distributed Electronic Health Record (2018) — 68 citations
- Active Learning for Coreference Resolution (2012) — 11 citations
- A Pronoun Anaphora Resolution System based on Factorial Hidden Markov Models (2011) — 18 citations