Christopher Ré | Academic Influence

Christopher Ré's AcademicInfluence.com Rankings

Christopher Ré

Computer Science

#1463

World Rank

#1513

Historical Rank

Database

#9099

World Rank

#9569

Historical Rank

computer-science Degrees

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Computer Science

Christopher Ré's Degrees

PhD Computer Science University of Washington
Masters Computer Science University of Washington
Bachelors Computer Science University of Washington

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Why Is Christopher Ré Influential?

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According to Wikipedia, Christopher Ré is an American computer scientist. He is currently employed by Stanford University, where he is an associate professor. He was awarded a MacArthur Fellowship in 2015. Ré specializes in big data analysis. He co-founded Lattice.io, a data mining and machine learning company that was acquired by Apple in May 2017.

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Christopher Ré's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Predicting non-small cell lung cancer prognosis by fully automated microscopic pathology image features (2016) (653)
Assessment of Convolutional Neural Networks for Automated Classification of Chest Radiographs. (2019) (138)
Association of Omics Features with Histopathology Patterns in Lung Adenocarcinoma. (2017) (82)
AMELIE speeds Mendelian diagnosis by matching patient phenotype and genotype to primary literature (2020) (34)
AMELIE accelerates Mendelian patient diagnosis directly from the primary literature (2017) (27)
Scatterbrain: Unifying Sparse and Low-rank Attention (2021) (24)
SKM-TEA: A Dataset for Accelerated MRI Reconstruction with Dense Image Labels for Quantitative Clinical Evaluation (2022) (23)
Classifying Non-Small Cell Lung Cancer Histopathology Types and Transcriptomic Subtypes using Convolutional Neural Networks (2019) (20)
Observational Supervision for Medical Image Classification Using Gaze Data (2021) (15)
Systematic Protein Prioritization for Targeted Proteomics Studies through Literature Mining. (2018) (15)
Cut out the annotator, keep the cutout: better segmentation with weak supervision (2021) (12)
Socratic Learning: Correcting Misspecified Generative Models using Discriminative Models (2016) (11)
Machine learning and deep analytics for biocomputing: Call for better explainability (2018) (10)
Noise2Recon: A Semi-Supervised Framework for Joint MRI Reconstruction and Denoising (2021) (9)
Multi-frame Weak Supervision to Label Wearable Sensor Data (2019) (8)
A Cloud-Based Metabolite and Chemical Prioritization System for the Biology/Disease-Driven Human Proteome Project. (2018) (8)
Similarity-based LSTMs for Time Series Representation Learning in the Presence of Structured Covariates (2016) (7)
Interpreting mental state decoding with deep learning models (2022) (4)
Weak supervision as an efficient approach for automated seizure detection in electroencephalography. (2020) (3)
Impact of Upstream Medical Image Processing on Downstream Performance of a Head CT Triage Neural Network. (2021) (3)
AMELIE 2 speeds up Mendelian diagnosis by matching patient phenotype & genotype to primary literature (2019) (2)
The Details Matter: Preventing Class Collapse in Supervised Contrastive Learning (2022) (2)
Improving Sample Complexity with Observational Supervision (2019) (1)
Predicting Non-Small Cell Lung Cancer Diagnosis and Prognosis by Fully Automated Microscopic Pathology Image Features (2017) (1)
Injection Drug Use and Healthcare Utilization in Patients Newly Diagnosed With HIV (2021) (1)
Lecture Notes on Weak Supervision (2019) (1)
Speeding up cardiac MR segmentation with semi-supervision: applications in cine imaging (2022) (1)
The 2nd Learning from Limited Labeled Data (LLD) Workshop: Representation Learning for Weak Supervision and Beyond (2019) (0)
Reducing Reliance on Spurious Features in Medical Image Classification with Spatial Specificity (2022) (0)
Unraveling the Molecular Basis of Lung Adenocarcinoma Dedifferentiation and Prognosis by Integrating Omics and Histopathology (2018) (0)
Automated Training Set Generation for Aortic Valve Classification (2017) (0)
LEARNING OPERATIONS FOR NEURAL PDE SOLVERS (0)
A Machine-Curated Database of Genome-Wide 1 Association Studies 2 (2018) (0)
Benchmarking explanation methods for mental state decoding with deep learning models (2023) (0)
Socratic Learning: Empowering the Generative Model (2016) (0)

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