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Computer Science

D-Index
31
Citations
6838
World Ranking
13398
National Ranking
213

Overview

Emmanuel Abbe is affiliated with the École Polytechnique Fédérale de Lausanne in Switzerland. Their research spans several areas primarily within computer science and medicine, with a focus on artificial intelligence and diagnostic imaging.

Their body of work includes contributions to key topics such as:

  • Neural Networks and Applications
  • Cardiac Imaging and Diagnostics
  • DNA and Biological Computing
  • Machine Learning and Algorithms
  • Error Correcting Code Techniques
  • Coronary Interventions and Diagnostics
  • Stochastic Gradient Optimization Techniques

Main fields of study covered in their publications are:

  • Computer Science
  • Medicine

More specific subfields within these domains include:

  • Artificial Intelligence
  • Radiology, Nuclear Medicine and Imaging
  • Molecular Biology
  • Statistics and Probability
  • Computer Networks and Communications

Emmanuel Abbe has published extensively in the following venues:

  • arXiv (Cornell University)
  • IEEE Transactions on Information Theory
  • The Annals of Statistics
  • European Heart Journal
  • EuroIntervention

Notable recent papers authored by Emmanuel Abbe include:

  • Entrywise eigenvector analysis of random matrices with low expected rank, 2020, The Annals of Statistics
  • Reed-Muller Codes: Theory and Algorithms, 2020, IEEE Transactions on Information Theory
  • Reed-Muller Codes Polarize, 2020, IEEE Transactions on Information Theory

Other frequently cited works connected to their field of study include:

  • ChatGPT takes on the European Exam in Core Cardiology: an artificial intelligence success story?, 2023, European Heart Journal - Digital Health
  • Recursive Projection-Aggregation Decoding of Reed-Muller Codes, 2020, IEEE Transactions on Information Theory

Frequent co-authors collaborating with Emmanuel Abbe are:

  • Olivier Müller
  • Stéphane Fournier
  • Thabo Mahendiran
  • Dorina Thanou
  • Ortal Senouf

Best Publications

  • Community detection and stochastic block models: recent developments

    Emmanuel Abbe

  • Community Detection and Stochastic Block Models

    Emmanuel Abbe

  • Exact Recovery in the Stochastic Block Model

    Emmanuel Abbe;Afonso S. Bandeira;Georgina Hall

  • Community Detection in General Stochastic Block models: Fundamental Limits and Efficient Algorithms for Recovery

    Emmanuel Abbe;Colin Sandon

  • ENTRYWISE EIGENVECTOR ANALYSIS OF RANDOM MATRICES WITH LOW EXPECTED RANK.

    Emmanuel Abbe;Jianqing Fan;Kaizheng Wang;Yiqiao Zhong

  • Communication-Computation Efficient Gradient Coding

    Min Ye;Emmanuel Abbe

  • Decoding Binary Node Labels from Censored Edge Measurements: Phase Transition and Efficient Recovery

    Emmanuel Abbe;Afonso S. Bandeira;Annina Bracher;Amit Singer

  • Polar Coding for Secret-Key Generation

    Remi A. Chou;Matthieu R. Bloch;Emmanuel Abbe

  • Polar Codes for the m-User MAC

    Emmanuel Abbe;Emre Telatar

  • Community detection in general stochastic block models: fundamental limits and efficient recovery algorithms.

    Emmanuel Abbe;Colin Sandon

  • Polar Codes for Broadcast Channels

    Naveen Goela;Emmanuel Abbe;Michael Gastpar

  • Detection in the stochastic block model with multiple clusters: proof of the achievability conjectures, acyclic BP, and the information-computation gap

    Emmanuel Abbe;Colin Sandon

  • Asymptotic mutual information for the balanced binary stochastic block model

    Yash Deshpande;Emmanuel Abbe;Andrea Montanari

  • Recursive Projection-Aggregation Decoding of Reed-Muller Codes

    Min Ye;Emmanuel Abbe

  • Normalization and correlation of cross-nested logit models

    Emmanuel Abbe;Michel Bierlaire;Tomer Toledo

  • Exact Recovery in the Stochastic Block Model

    Emmanuel Abbe;Afonso S. Bandeira;Georgina Hall

  • Privacy-Preserving Methods for Sharing Financial Risk Exposures

    Emmanuel Auguste Abbe;Amir E. Khandani;Andrew W. Lo

  • Polar coding schemes for the AWGN channel

    Emmanuel Abbe;Andrew Barron

  • Recovering communities in the general stochastic block model without knowing the parameters

    Emmanuel Abbe;Colin Sandon

  • Asymptotic Mutual Information for the Two-Groups Stochastic Block Model

    Yash Deshpande;Emmanuel Abbe;Andrea Montanari

  • Proof of the Achievability Conjectures for the General Stochastic Block Model

    Emmanuel Abbe;Colin Sandon

  • Reed–Muller Codes: Theory and Algorithms

    Emmanuel Abbe;Amir Shpilka;Min Ye

  • Provable limitations of deep learning.

    Emmanuel Abbe;Colin Sandon

  • Reed–Muller Codes for Random Erasures and Errors

    Emmanuel Abbe;Amir Shpilka;Avi Wigderson

Frequent Co-Authors

Andrea Montanari
Andrea Montanari Stanford University
Amit Singer
Amit Singer Princeton University
Amir Shpilka
Amir Shpilka Tel Aviv University
Sanjeev R. Kulkarni
Sanjeev R. Kulkarni Princeton University
Nathan Srebro
Nathan Srebro Toyota Technological Institute at Chicago
Noga Alon
Noga Alon Tel Aviv University
Avi Wigderson
Avi Wigderson Institute for Advanced Study
Michael Gastpar
Michael Gastpar École Polytechnique Fédérale de Lausanne
Sergio Verdu
Sergio Verdu Princeton University

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