Home Page of Daphna Weinshall.

Daphna Weinshall


Professor
School of Computer Science and Engineering

Hebrew University of Jerusalem
Jerusalem 91904
Israel


daphna at cs huji ac il
+ 972-2-549-4542


Traveling (slideshows):

Selected publications

Recent Publications
Learning and Object Recongition
Computer Vision
Cognitive Neuroscience
Population Genetics


Data

EVAT: database of Emotionally evocative Video clips and their associated Affective Tagging
FIF: database of super Fine grained Israeli Flowers


Students

  • Tomer Yaacoby (2024-). M.Sc.
  • Danit Yanowsky (2024-). M.Sc.
  • Rom Maltser (2023-). M.Sc.
  • Shahar Ariel (2023-). M.Sc.
  • Elias Wakileh (2023-). M.Sc.
  • Inbal Mishaal (2022-). M.Sc.
  • Uri Stern (2022-2023). Observing and Correcting Overfit in Deep Neural Networks. pdf M.Sc.
  • Noam Fluss (2022-2023). Semi-Supervised Learning in the Few-Shot Zero-Shot Scenario. pdf M.Sc.
  • Guy Hacohen (2018-2023). Learning How Neural Networks Learn. pdf Ph.D.
  • Ofer Yehuda (2023). Active Learning Through a Covering Lens. pdf M.Sc.
  • Avihu Dekel (2022). Low Budget Active Learning: Theory and Algorithms. pdf M.Sc.
  • Daniel Schwartz (2022). The Dynamic of Consensus in Deep Networks and the Identification of Noisy Labels. pdf M.Sc.
  • Eran Zecharia (2022). Curriculum Learning on Fully Supervised and Semi-Supervised Classification Using Self-Supervised Representation Learning. M.Sc.
  • Lotan Levy (2021). Computational Divergent Thinking Using Visual Data. pdf M.Sc.
  • Itamar Winter (2020). Multiclass non-Adversarial Image Synthesis with Application to Classification from Very Small Sample. pdf M.Sc.
  • Roee Cates (2020). Self-Supervision Can Benefit Fully-Supervised Classification Tasks. pdf M.Sc.
  • Boaz Lerner (2020). Boosting the Performance of Semi-Supervised Learning with Unsupervised Clustering. pdf M.Sc.
  • Guy Shiran (2020). Multi-Modal Deep Clustering: Unsupervised Partitioning of Images. pdf M.Sc.
  • Idan Azuri (2020). Learning from Small Data Through Sampling an Implicit Conditional Generative Latent Optimization Model. pdf M.Sc.
  • Gregory Pasternak (2020). Non-Uniform Batch Sampling for Relaxed Curriculum-based Learning. pdf M.Sc.
  • Matan Ben-Yosef (2018). Multi-Modal Generative Adversarial Networks. pdf M.Sc.
  • Haim Dubossarsky (2018). Semantic change at large: A computational approach for semantic change research. pdf Ph.D.
  • Ravid Cohen (2018). Mixture of Convolutional Neural Networks for Image Classification. pdf M.Sc.
  • Gad Cohen (2018). Hidden Layers in Perceptual Learning. pdf M.Sc.
  • Talia Tron (2017). Automated Facial Expressions Analysis in Schizophrenia: a Continuous Dynamic Approach. pdf Ph.D.
  • Yehezkel Resheff (2017). A Machine Learning Approach to Analysis of Biologger Data in Movement Ecology. pdf Ph.D.
  • Amit Mandelbaum (2017). Distance-based Confidence Score for Neural Network Classifiers. pdf M.Sc.
  • Tamar Elazari (2017). Face Verfication and Face Image Synthesis under Illumination Changes using Neural Networks. M.Sc. pdf
  • Daniel Hadar (2016). Implicit Media Tagging and Affect Prediction from video of spontaneous facial expressions, recorded with depth camera. M.Sc. pdf
  • Nomi Vinokurov (2016). Novelty Detection in MultiClass Scenarios with Incomplete Set of Class Labels. M.Sc. pdf
  • Lior Bar (2015). Multiclass Classification: Margins Revisited, Novelty Detection via Trees, and Visual Object Recognition with Sparse Features Derived from a Convolution Neural Net. M.Sc. pdf
  • Uri Shalit (2014). Scalable Streaming Learning of Dyadic Relationships. Ph.D. pdf
  • Alon Cohen (2014). Surrogate Loss Minimization. M.Sc. pdf
  • Alon Zweig (2013). Hierarchical Modeling and Applications to Recognition Tasks. Ph.D. pdf
  • Roi Kliper (2013). Learning Distance Functions to Gain Insights into Functional Representations of Complex Objects in the Brain. Ph.D. pdf
  • Gal Levi (2013). Latent Dirichlet Allocation with Soft Assignment of Descriptors to Words. M.Sc. pdf
  • Dmitri Hanukaev (2013). LDA Topic Model with Soft Assignment of Descriptors to Words. M.Sc.
  • Avishai Hendel (2012). Identifying Surprising Events in Videos Using Bayesian Topic Models. M.Sc. pdf
  • Avram Golbert (2012). Object Detection from Multiple Overlapping Views Using Semantic and Geometric Context in 3D. M.Sc. pdf
  • Amir Rosenfeld (2011). Extracting Foreground Masks towards Object Recognition. M.Sc. pdf
  • Dagan Eshar (2009). Generative Implementation of Hierarchical Novelty Detector. M.Sc. pdf
  • Tomer Hertz (2007). Learning Distance Functions with Applications in Image Retrieval, Clustering, Classification and Immunoinformatics. Ph.D. pdf
  • Lior Zamir (2007). Feature Selection in Distance Learning from Small Sample. M.Sc. pdf
  • Aharon Bar-Hillel (2006). Learning from Weak Representations using Distance Functions and Generative Models. Ph.D. pdf
  • Anna Sorkin (2006). Virtual Reality for Diagnostic Assessment of Schizophrenia Deficits. Ph.D. pdf
  • Doron Feldman (2006). Analyzing the Spatio-Temporal Domain: from View Synthesis to Motion Segmentation. Ph.D. pdf
  • Vered Tsedaka (2005). Data Modeling with Gaussian Mixture Based Clustering: A Unifying View for Discriminative and Generative Clustering. M.Sc. pdf
  • Inna Weiner (2005). Analyzing Auditory Neurons by Learning Distance Functions. M.Sc. pdf
  • Adam Spiro (2005). Bayesian Clustering of non-stationary Data. M.Sc. pdf
  • Noam Shental (2004). From Unsupervised to Semi-Supervised Learning: Algorithms and Applications. Ph.D. pdf
  • Yoram Gdalyahu (1999). Stochastic Clustering and its Applications to Computer Vision. Ph.D. pdf
  • Gilad Halevy (1997). Motion of disturbances: detection and tracking of multi-body non rigid motion. M.Sc.

    • Recorded lectures:

    June 2010: Category Learning from Equivalence Constraints mp4
    Oct 2011: Identifying Surprising Events in Videos mp4
    Feb 2019: On the Power of Curriculum Learning in Training Deep Networks: mp4, online link


    Biography:

    Brief Biography
    Curriculum Vita


    Teaching:

    visual Visual Object Recognition 2009 [67777]
    Introduction to Computer Science 2009/10 [67101]


    A few demos:

    Test yourself: depth ordering
    Schizophrenia profile: incoherencies detection
    Image-based rendering: X-slits movies
    Image-based rendering: bi-centric movies
    Gesture recognition: pointing target detection
    Curve matching: demo
    Tracking: multi-body motion
    Tracking: storms


    Code (usually matlab):

  • Figure-ground segregation, see paper.
  • DistBoost - a boosting-based distance learning algorithm, see paper.
  • Constrained EM algorithm: full package (with BNT) and minimal code, see paper.
  • RCA Mahalanobis distance learning, see paper.
  • Typical-cut clustering algorithm (in C), see paper.
  • Relational model learning, see paper.
  • Spike sorting - Clustering of non-stationary data, see paper.


    • Research Interests:

    Computer and human vision
    Machine and perceptual learning


    My best results - Yael and Tom:

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