A Parameter-efficient Multi-subject Model for Predicting fMRI Activity

Encoding and decoding in fmri

Thomas Naselaris, Kendrick N Kay, Shinji Nishimoto, and Jack L Gallant · 2011

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Pycortex: an interactive surface visualizer for fmri

James S Gao, Alexander G Huth, Mark D Lescroart, and Jack L Gallant · 2015

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Xception: Deep learning with depthwise separable convolutions

François Chollet · 2017

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Bohb: Robust and efficient hyperparameter optimization at scale

Stefan Falkner, Aaron Klein, and Frank Hutter · 2018

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Pytorch image models, 2019

Ross Wightman et al · 2019

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Experiment tracking with weights and biases, 2020

Lukas Biewald · 2020

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An image is worth 16x16 words: Transformers for image recognition at scale

Original

Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020

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Beit: Bert pre-training of image transformers

Original

Hangbo Bao, Li Dong, Songhao Piao, and Furu Wei · 2021

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Emerging properties in self-supervised vision transformers

Mathilde Caron, Hugo Touvron, Ishan Misra, Hervé Jégou, Julien Mairal, Piotr Bojanowski, and Armand Joulin · 2021

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Learning transferable visual models from natural language supervision

Alec Radford, Jong Wook Kim, Chris Hallacy, Aditya Ramesh, Gabriel Goh, Sandhini Agarwal, Girish Sastry, Amanda Askell, Pamela Mishkin, Jack Clark, et al · 2021

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Laion-400m: Open dataset of clip-filtered 400 million image-text pairs

Original

Christoph Schuhmann, Richard Vencu, Romain Beaumont, Robert Kaczmarczyk, Clayton Mullis, Aarush Katta, Theo Coombes, Jenia Jitsev, and Aran Komatsuzaki · 2021

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A massive 7t fmri dataset to bridge cognitive neuroscience and artificial intelligence

Emily J Allen, Ghislain St-Yves, Yihan Wu, Jesse L Breedlove, Jacob S Prince, Logan T Dowdle, Matthias Nau, Brad Caron, Franco Pestilli, Ian Charest, et al · 2022

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What can 1.8 billion regressions tell us about the pressures shaping high-level visual representation in brains and machines?

Reproducible scaling laws for contrastive language-image learning

Mehdi Cherti, Romain Beaumont, Ross Wightman, Mitchell Wortsman, Gabriel Ilharco, Cade Gordon, Christoph Schuhmann, Ludwig Schmidt, and Jenia Jitsev · 2023

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Eva-02: A visual representation for neon genesis

Original

Yuxin Fang, Quan Sun, Xinggang Wang, Tiejun Huang, Xinlong Wang, and Yue Cao · 2023

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Eva: Exploring the limits of masked visual representation learning at scale

Yuxin Fang, Wen Wang, Binhui Xie, Quan Sun, Ledell Wu, Xinggang Wang, Tiejun Huang, Xinlong Wang, and Yue Cao · 2023

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The algonauts project 2023 challenge: How the human brain makes sense of natural scenes

Original

Alessandro T Gifford, Benjamin Lahner, Sari Saba-Sadiya, Martina G Vilas, Alex Lascelles, Aude Oliva, Kendrick Kay, Gemma Roig, and Radoslaw M Cichy · 2023

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Dinov2: Learning robust visual features without supervision