Marco A. F. Pimentel

Artificial Intelligence · 2014–2018

A researcher in the Science corpus: 5 papers; trusts 21 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 57 citations into it; #20,640 of 35,345 by trust here, #10,319 by citations
• Computer Networks and Communications — 18 citations into it; #5,255 of 9,886 by trust here, #1,912 by citations
• Signal Processing — 16 citations into it
• Biomedical Engineering — 14 citations into it; #3,961 of 10,734 by trust here, #5,210 by citations
• Probabilistic & Bayesian Methods — 11 citations into it
• Epidemiology — 9 citations into it
• Control and Systems Engineering — 8 citations into it
• Medical & Health AI — 5 citations into it

Whom Marco A. F. Pimentel trusts overall

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

1. Yoshua Bengio
2. Dit-Yan Yeung
3. Christopher Krügel
4. Emanuel Parzen
5. Geoffrey E. Hinton
6. Markos Markou
7. Radford M. Neal
8. Neil D. Lawrence
9. Geoffrey J. McLachlan
10. Matthew V. Mahoney

Who trusts Marco A. F. Pimentel overall

1. Eric T. Nalisnick
2. Anastasios Nikolas Angelopoulos
3. Joseph D. Futoma
4. Li-Fang Cheng
5. Yinhe Zheng
6. Akihiro Matsukawa
7. Rémi Domingues
8. Marzyeh Ghassemi
9. Alistair E. W. Johnson
10. Stephen Bates

Papers from Marco A. F. Pimentel's perspective

Ordered by how strongly the researchers Marco A. F. Pimentel trusts endorse each paper. Same corpus, a different order for every researcher.

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

Their papers

• A review of novelty detection (2014) — 1,664 citations
• Multitask Gaussian Processes for Multivariate Physiological Time-Series Analysis (2015) — 167 citations
• A Multivariate Timeseries Modeling Approach to Severity of Illness Assessment and Forecasting in ICU with Sparse, Heterogeneous Clinical Data (2015) — 238 citations
• Breathing Rate Estimation From the Electrocardiogram and Photoplethysmogram: A Review (2017) — 338 citations
• Predicting in-hospital mortality and unanticipated admissions to the intensive care unit using routinely collected blood tests and vital signs: Development and validation of a multivariable model (2018) — 42 citations