Gal Chechik

7.5k citations

106 papers · 3.7k indexed · 2 hit papers · h-index 31

Impact in

Computer Vision and Pattern Recognition top 0.5%
- Advanced Image and Video Retrieval Techniques
- Multimodal Machine Learning Applications
- Generative Adversarial Networks and Image Synthesis
- Image Retrieval and Classification Techniques
Cognitive Neuroscience top 2%
- Neural dynamics and brain function
- Neuroscience and Music Perception

Papers in ⓘ

Computer Vision and Pattern Recognition 44
- Multimodal Machine Learning Applications 17
- Image Retrieval and Classification Techniques 13
- Advanced Image and Video Retrieval Techniques 11
Artificial Intelligence 40
- Domain Adaptation and Few-Shot Learning 17
- Machine Learning and Algorithms 8

Co-authors: Samy Bengio (7 shared papers)Uri Shalit (10 shared papers)Naftali Tishby (7 shared papers)Israel Nelken (4 shared papers)Varun Sharma (3 shared papers)Daphne Koller (5 shared papers)Yuval Atzmon (12 shared papers)Isaac Meilijson (6 shared papers)
Journals: Neural Computation (5 papers)ACM Transactions on Graphics (4 papers)PLoS Computational Biology (4 papers)Journal of Machine Learning Research (4 papers)Neurocomputing (3 papers)
Partner nations: Israel United States United Kingdom

In The Last Decade

Gal Chechik

99 papers receiving 3.6k citations

Hit Papers

align trajectories log scale

Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models 2023 · 87 citations

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if any of the following hold:

it has ≥500 total citations;
it reaches ≥1.5× the top-1% citation threshold for papers in the same subfield and year (the threshold is the minimum needed to enter the top 1%, not the average within it);
it reaches the top citation threshold in at least one of its specific research topics.

2023 ACM Transactions on Graphics
2022 ACM Transactions on Graphics

Peers

Countries citing papers authored by Gal Chechik

Since Specialization

Citations

This map shows the geographic impact of Gal Chechik's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Gal Chechik with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Gal Chechik more than expected).

Fields of papers citing papers by Gal Chechik

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Gal Chechik. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Gal Chechik. The network helps show where Gal Chechik may publish in the future.

Co-authors

The 25 scholars most cited alongside Gal Chechik, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Gal Chechik Line = papers co-authored together Gal Chechik links everyone, so they are left out of the graph.

All Works

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20 of 20 papers shown

Showing the 20 most-cited of 106 papers — load more, or switch the sort, to bring in the rest.

#	Work
1	Large Scale Online Learning of Image Similarity through Ranking Journal of Machine Learning Research ·Gal Chechik, Varun Sharma, Uri Shalit, Samy Bengio	2009	299
2	StyleGAN-NADA ACM Transactions on Graphics ·Rinon Gal, Or Patashnik, Haggai Maron, Amit H. Bermano, Gal Chechik, Daniel Cohen‐Or Hit paper breakdown →	2022	269
3	Learning from Noisy Large-Scale Datasets with Minimal Supervision Andreas Veit, Neil Alldrin, Gal Chechik, Ivan Krasin, Abhinav Gupta, Serge Belongie	2017	264
4	Functional Organization of the S. cerevisiae Phosphorylation Network Cell ·Dorothea Fiedler, Hannes Braberg, Monika Mehta, Gal Chechik, Gerard Cagney, Paromita Mukherjee, Andréa C. Silva, Michael Shales, Sean R. Collins, Sake van Wageningen, Patrick Kemmeren, Frank C. P. Holstege, Jonathan S. Weissman, Michael‐Christopher Keogh, Daphne Koller, Kevan M. Shokat, Nevan J. Krogan	2009	205
5	Reduction of Information Redundancy in the Ascending Auditory Pathway Neuron ·Gal Chechik, Michael J. Anderson, Omer Bar‐Yosef, Eric D. Young, Naftali Tishby, Israel Nelken	2006	178
6	A unifying principle underlying the extracellular field potential spectral responses in the human cortex Journal of Neurophysiology ·Ella Podvalny, Niv Noy, Michal Harel, Stephan Bickel, Gal Chechik, Charles E. Schroeder, Ashesh D. Mehta, Misha Tsodyks, Rafael Malach	2015	150
7	Activity motifs reveal principles of timing in transcriptional control of the yeast metabolic network Nature Biotechnology ·Gal Chechik, Eugene Oh, Oliver J. Rando, Jonathan S. Weissman, Aviv Regev, Daphne Koller	2008	130
8	Encoding Stimulus Information by Spike Numbers and Mean Response Time in Primary Auditory Cortex Journal of Computational Neuroscience ·Israel Nelken, Gal Chechik, Thomas D. Mrsic‐Flogel, Andrew J. King, Jan W. H. Schnupp	2005	114
9	Neuronal Regulation: A Mechanism for Synaptic Pruning During Brain Maturation Neural Computation ·Gal Chechik, Isaac Meilijson, Eytan Ruppin	1999	112
10	Synaptic Pruning in Development: A Computational Account Neural Computation ·Gal Chechik, Isaac Meilijson, Eytan Ruppin	1998	112
11	Euclidean Embedding of Co-Occurrence Data Journal of Machine Learning Research ·Amir Globerson, Gal Chechik, Fernando Pereira, Naftali Tishby	2004	106
12	Self-Supervised Learning for Domain Adaptation on Point Clouds Idan Achituve, Haggai Maron, Gal Chechik	2021	101
13	Max-margin Classification of Data with Absent Features Gal Chechik, Geremy Heitz, Gal Elidan, Pieter Abbeel, Daphne Koller	2008	91
14	Encoder-based Domain Tuning for Fast Personalization of Text-to-Image Models ACM Transactions on Graphics ·Rinon Gal, Moab Arar, Yuval Atzmon, Amit H. Bermano, Gal Chechik, Daniel Cohen‐Or Hit paper breakdown →	2023	87
15	DETReg: Unsupervised Pretraining with Region Priors for Object Detection 2022 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) ·Amir Bar, Xin Wang, Vadim Kantorov, Colorado Reed, Roei Herzig, Gal Chechik, Anna Rohrbach, Trevor Darrell, Amir Globerson	2022	80
16	Timing of Gene Expression Responses to Environmental Changes Journal of Computational Biology ·Gal Chechik, Daphne Koller	2009	76
17	Adaptive Confidence Smoothing for Generalized Zero-Shot Learning Yuval Atzmon, Gal Chechik	2019	72
18	An Online Algorithm for Large Scale Image Similarity Learning neural information processing systems ·Gal Chechik, Uri Shalit, Varun Sharma, Samy Bengio	2009	69
19	Context-Aware Captions from Context-Agnostic Supervision Ramakrishna Vedantam, Samy Bengio, Kevin Murphy, Devi Parikh, Gal Chechik	2017	69
20	Large-scale content-based audio retrieval from text queries Gal Chechik, Eugene Ie, Martin Rehn, Samy Bengio, Dick Lyon	2008	66

About Gal Chechik

Gal Chechik is a scholar working on Computer Vision and Pattern Recognition, Artificial Intelligence, Cognitive Neuroscience, Molecular Biology and Cellular and Molecular Neuroscience, having authored 106 papers that have together received 3.7k indexed citations. Recurring topics across this work include Domain Adaptation and Few-Shot Learning (17 papers), Multimodal Machine Learning Applications (17 papers), Neural dynamics and brain function (17 papers), Image Retrieval and Classification Techniques (13 papers), Neuroscience and Neuropharmacology Research (11 papers), Advanced Image and Video Retrieval Techniques (11 papers), Music and Audio Processing (10 papers) and Machine Learning and Algorithms (8 papers). The work is most often cited by research in Computer Vision and Pattern Recognition (1.4k citations), Cognitive Neuroscience (790 citations), Artificial Intelligence (1.2k citations), Computer Graphics and Computer-Aided Design (128 citations) and Computational Mathematics (17 citations). Gal Chechik has collaborated with scholars based in Israel, United States and United Kingdom. Frequent co-authors include Samy Bengio, Uri Shalit, Naftali Tishby, Israel Nelken, Varun Sharma, Daphne Koller, Yuval Atzmon, Isaac Meilijson, Eytan Ruppin and Rinon Gal. Their work appears in journals such as Neural Computation, ACM Transactions on Graphics, PLoS Computational Biology, Journal of Machine Learning Research and Neurocomputing.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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