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Christopher Ré

58 papers hereh-index 5314.7k citations125 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author25
  • last author31

Across the 56 of 58 papers where every author was matched, so the position is known.

fields
  • cs.LG33
  • cs.CL6
  • eess.IV3
  • stat.ML3
  • cs.CV2
  • cs.DB2
same name
  • Christopher Ré — 14 papers, h 11
  • Christopher Ré — 10 papers, h 5
  • Christopher Ré — 5 papers
  • Christopher Ré — 3 papers, h 4
  • Christopher Ré — 3 papers, h 2
  • Christopher Ré — 3 papers, h 4

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20152023
most citedHyperbolic Graph Convolutional Neural Networks

266 citations · 1.2k across the 39 of their papers we have counts for

collaborators
Showing 2019 · cs.LGShow all

4 papers · 2 filters

cs.LG2019★ 266 cited

Hyperbolic Graph Convolutional Neural Networks

Ines Chami, Rex Ying, Christopher Ré +1

Graph convolutional neural networks (GCNs) embed nodes in a graph into Euclidean space, which has been shown to incur a large distortion when embedding real-world graphs with scale…

cs.LG2019

Hidden Stratification Causes Clinically Meaningful Failures in Machine Learning for Medical Imaging

Luke Oakden-Rayner, Jared Dunnmon, Gustavo Carneiro +1

Machine learning models for medical image analysis often suffer from poor performance on important subsets of a population that are not identified during training or testing. For e…

cs.LG2019

MLSys: The New Frontier of Machine Learning Systems

Alexander Ratner, Dan Alistarh, Gustavo Alonso +66

Machine learning (ML) techniques are enjoying rapidly increasing adoption. However, designing and implementing the systems that support ML models in real-world deployments remains…

cs.LG2019

Cross-Modal Data Programming Enables Rapid Medical Machine Learning

Jared Dunnmon, Alexander Ratner, Nishith Khandwala +8

Labeling training datasets has become a key barrier to building medical machine learning models. One strategy is to generate training labels programmatically, for example by applyi…

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