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Computer Science

D-Index
51
Citations
9427
World Ranking
5382
National Ranking
85

Overview

Daphna Weinshall is affiliated with the Hebrew University of Jerusalem in Israel. Their research focuses primarily within the field of Computer Science, with specific interest in Artificial Intelligence, Computer Vision and Pattern Recognition, Radiology, Nuclear Medicine and Imaging, Cognitive Neuroscience, and Cultural Studies.

Their scholarly contributions include work on the following topics:

  • Domain Adaptation and Few-Shot Learning
  • Machine Learning and Data Classification
  • Neural Networks and Applications
  • Advanced Neural Network Applications
  • Multimodal Machine Learning Applications
  • Machine Learning and Algorithms
  • COVID-19 diagnosis using AI

Weinshall's publication record includes numerous papers primarily disseminated through arXiv (Cornell University), Proceedings of the AAAI Conference on Artificial Intelligence, and the Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers).

Selected recent papers are as follows:

  • Active Learning on a Budget: Opposite Strategies Suit High and Low Budgets, 2022, arXiv (Cornell University)
  • Active Learning Through a Covering Lens, 2022, arXiv (Cornell University)
  • The Grammar-Learning Trajectories of Neural Language Models, 2022, Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  • United We Stand: Using Epoch-Wise Agreement of Ensembles to Combat Overfit, 2024, Proceedings of the AAAI Conference on Artificial Intelligence
  • Principal Components Bias in Over-parameterized Linear Models, and its Manifestation in Deep Neural Networks, 2021, arXiv (Cornell University)

Their frequent collaborators include the following researchers:

  • Guy Hacohen
  • Uri Stern
  • Daniel Shwartz
  • Avihu Dekel
  • Leshem Choshen

Weinshall has published extensively in the domain of computer science with a total of 46 publications, out of which 32 focus on artificial intelligence and 12 on computer vision and pattern recognition. Their work also spans medical imaging fields and interdisciplinary areas such as cognitive neuroscience and cultural studies.

Best Publications

  • Learning a Mahalanobis Metric from Equivalence Constraints

    Aharon Bar-Hillel;Tomer Hertz;Noam Shental;Daphna Weinshall

  • Learning distance functions using equivalence relations

    Aharon Bar-Hillel;Tomer Hertz;Noam Shental;Daphna Weinshall

  • Computing Gaussian Mixture Models with EM Using Equivalence Constraints

    Noam Shental;Aharon Bar-hillel;Tomer Hertz;Daphna Weinshall

  • Flexible syntactic matching of curves and its application to automatic hierarchical classification of silhouettes

    Y. Gdalyahu;D. Weinshall

  • Adjustment Learning and Relevant Component Analysis

    Noam Shental;Tomer Hertz;Daphna Weinshall;Misha Pavel

  • Classification with nonmetric distances: image retrieval and class representation

    D.W. Jacobs;D. Weinshall;Y. Gdalyahu

  • Self-organization in vision: stochastic clustering for image segmentation, perceptual grouping, and image database organization

    Y. Gdalyahu;D. Weinshall;M. Werman

  • Cognitive authentication schemes safe against spyware

    D. Weinshall

  • On The Power of Curriculum Learning in Training Deep Networks.

    Guy Hacohen;Daphna Weinshall

  • Mosaicing new views: the Crossed-Slits projection

    A. Zomet;D. Feldman;S. Peleg;D. Weinshall

  • A self-organizing multiple-view representation of 3D objects

    Daphna Weinshall;Shimon Edelman;Heinrich H. Bülthoff

  • Computer vision-based wireless pointing system

    Antonio J. Colmenarez;Eric Cohen-Solal;Daphna Weinshall;Mi-Suen Lee

  • Passwords you'll never forget, but can't recall

    Daphna Weinshall;Scott Kirkpatrick

  • Mechanisms of generalization in perceptual learning.

    Zili Liu;Daphna Weinshall

  • Exploiting Object Hierarchy: Combining Models from Different Category Levels

    A. Zweig;D. Weinshall

  • Outta Control: Laws of Semantic Change and Inherent Biases in Word Representation Models.

    Haim Dubossarsky;Daphna Weinshall;Eitan Grossman

  • Linear and incremental acquisition of invariant shape models from image sequences

    D. Weinshall;C. Tomasi

  • Linear and incremental acquisition of invariant shape models from image sequences

    D. Weinshall;C. Tomas

  • Similarity and affine invariant distances between 2D point sets

    M. Werman;D. Weinshall

  • Learning distance functions for image retrieval

    T. Hertz;A. Bar-Hillel;D. Weinshall

Frequent Co-Authors

Michael Werman
Michael Werman Hebrew University of Jerusalem
Shaul Hochstein
Shaul Hochstein Hebrew University of Jerusalem
Shimon Edelman
Shimon Edelman Cornell University
Heinrich H. Bülthoff
Heinrich H. Bülthoff Max Planck Institute for Biological Cybernetics
Shmuel Peleg
Shmuel Peleg Hebrew University of Jerusalem
Frank W. Ohl
Frank W. Ohl Leibniz Institute for Neurobiology
Miroslav Trajkovic
Miroslav Trajkovic Zebra Technologies (United States)
Misha Pavel
Misha Pavel Northeastern University
David W. Jacobs
David W. Jacobs University of Maryland, College Park

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