no code implementations • 31 Oct 2024 • Colin Conwell, Christopher Hamblin, Chelsea Boccagno, David Mayo, Jesse Cummings, Leyla Isik, Andrei Barbu
We show that unimodal vision models (e. g. SimCLR) account for the vast majority of explainable variance in these ratings.
2 code implementations • 22 Aug 2024 • Haojun Shi, Suyu Ye, Xinyu Fang, Chuanyang Jin, Leyla Isik, Yen-Ling Kuo, Tianmin Shu
To truly understand how and why people interact with one another, we must infer the underlying mental states that give rise to the social interactions, i. e., Theory of Mind reasoning in multi-agent interactions.
no code implementations • 19 Feb 2024 • Gunnar Blohm, Benjamin Peters, Ralf Haefner, Leyla Isik, Nikolaus Kriegeskorte, Jennifer S. Lieberman, Carlos R. Ponce, Gemma Roig, Megan A. K. Peters
Generative adversarial collaborations (GACs) are a form of formal teamwork between groups of scientists with diverging views.
no code implementations • 11 Jan 2024 • Benjamin Peters, James J. DiCarlo, Todd Gureckis, Ralf Haefner, Leyla Isik, Joshua Tenenbaum, Talia Konkle, Thomas Naselaris, Kimberly Stachenfeld, Zenna Tavares, Doris Tsao, Ilker Yildirim, Nikolaus Kriegeskorte
The alternative conception is that of vision as an inference process in Helmholtz's sense, where the sensory evidence is evaluated in the context of a generative model of the causal processes giving rise to it.
1 code implementation • Nature Communications 2023 • Manasi Malik, Leyla Isik
However, growing behavioral and neuroscience evidence suggests that recognizing social interactions is a visual process, separate from complex mental state inference.
no code implementations • 23 Aug 2022 • Anna A. Ivanova, Martin Schrimpf, Stefano Anzellotti, Noga Zaslavsky, Evelina Fedorenko, Leyla Isik
Moreover, we argue that, instead of categorically treating the mapping models as linear or nonlinear, we should instead aim to estimate the complexity of these models.
no code implementations • 19 Jan 2022 • Ashwin De Silva, Rahul Ramesh, Lyle Ungar, Marshall Hussain Shuler, Noah J. Cowan, Michael Platt, Chen Li, Leyla Isik, Seung-Eon Roh, Adam Charles, Archana Venkataraman, Brian Caffo, Javier J. How, Justus M Kebschull, John W. Krakauer, Maxim Bichuch, Kaleab Alemayehu Kinfu, Eva Yezerets, Dinesh Jayaraman, Jong M. Shin, Soledad Villar, Ian Phillips, Carey E. Priebe, Thomas Hartung, Michael I. Miller, Jayanta Dey, Ningyuan, Huang, Eric Eaton, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Randal Burns, Onyema Osuagwu, Brett Mensh, Alysson R. Muotri, Julia Brown, Chris White, Weiwei Yang, Andrei A. Rusu, Timothy Verstynen, Konrad P. Kording, Pratik Chaudhari, Joshua T. Vogelstein
We conjecture that certain sequences of tasks are not retrospectively learnable (in which the data distribution is fixed), but are prospectively learnable (in which distributions may be dynamic), suggesting that prospective learning is more difficult in kind than retrospective learning.
no code implementations • NeurIPS Workshop SVRHM 2020 • Paul Soulos, Leyla Isik
We further find that the latent dimensions in these models map onto non-overlapping regions in fMRI data, allowing us to "disentangle" different features such as 3D rotation, skin tone, and facial expression in the human brain.
no code implementations • 6 Jun 2014 • Tomaso Poggio, Jim Mutch, Leyla Isik
From the slope of the inverse of the magnification factor, M-theory predicts a cortical "fovea" in V1 in the order of $40$ by $40$ basic units at each receptive field size -- corresponding to a foveola of size around $26$ minutes of arc at the highest resolution, $\approx 6$ degrees at the lowest resolution.