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Posts by Tal Golan

Israeli STEM postdocs abroad, have a look at this fellowship:

www.gov.il/he/pages/rfp...

24 months x 13,500 NIS, Deadline: March 24, 2026

If you are working at the intersection of deep learning and cognitive (neuro)science, I'd be happy to host.

2 months ago 1 0 0 0

We are excited to announce that the Cognitive Computational Neuroscience meeting (CCN 2026) will be held at New York University from August 3–6, 2026.
2026.ccneuro.org

4 months ago 75 29 1 0

Proud to share our lab’s first paper! Itamar’s work highlights an implicit but impactful tension between maximizing fit to behavioral data and staying sensitive to meaningful differences between neural network models.

5 months ago 7 1 0 0
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Variance partitioning is used to quantify the overlap of two models. Over the years, I have found that this can be a very confusing and misleading concept. So we finally we decided to write a short blog to explain why.
@martinhebart.bsky.social @gallantlab.org
diedrichsenlab.org/BrainDataSci...

7 months ago 66 22 2 5
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We’re hiring in my dept. (IEM @ Ben-Gurion Univ.)! Tenure-track faculty opening in Robotics, Data/ML, Info Systems, Applied Stats, Production Systems, or Human Factors. www.bgu.ac.il/media/wwfbuc...
Please repost 🙏

7 months ago 2 1 0 0
An illustration of our approach using an example from a database of line drawings of natural scenes. In this pipeline, we first extract line drawings of the input image, then its Medial Axis Transform (MAT) is computed and then the skeletal points on the MAT are scored based upon one of our importance score measures. Finally, they are projected back onto the contours. The figure on the top left shows an example scene used in our pipeline, and the figure below presents the jet colormap visualization of its contours using our medial axis-based contour importance measures.

An illustration of our approach using an example from a database of line drawings of natural scenes. In this pipeline, we first extract line drawings of the input image, then its Medial Axis Transform (MAT) is computed and then the skeletal points on the MAT are scored based upon one of our importance score measures. Finally, they are projected back onto the contours. The figure on the top left shows an example scene used in our pipeline, and the figure below presents the jet colormap visualization of its contours using our medial axis-based contour importance measures.

Shape-Based Measures Improve Scene Categorization by DNNs.

Morteza Rezanejad's magnus opus finally out in IEEE PAMI. doi.org/10.1109/TPAM...

A super productive and fun collaboration with John Wilder, Allan D. Jepson, Sven Dickinson, and Kaleem Siddiqi.

Read on for a quick summary.

2 years ago 2 4 3 0