dec 10-15, 2024
Neural Information Processing Systems 2024
Several members of the Kreiman lab presented their cutting-edge research at NeurIPS 2024.
6543092
NeurIPS2024
1
apa
50
date
1017
https://kreimanlab.com/wp-content/plugins/zotpress/
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Madan, S., Li, Y., Zhang, M., Pfister, H., & Kreiman, G. (2024). Improving generalization by mimicking the human visual diet. bioRxiv, 2206.07802. https://drive.google.com/file/d/17NhH3cw-cYB9pM2bOdnrkSUNlKR_KbWt/view?usp=sharing
Madan, S., Xiao, W., Cao, M., Pfister, H., Livingstone, M., & Kreiman, G. (2024). Benchmarking out-of-distribution generalization capabilities of DNN-based encoding models for the ventral visual cortex. NeurIPS. https://drive.google.com/file/d/1JlzUPI_5BQ1OmPj2e67ZXdv-YJorBWHZ/view?usp=sharing
Wang, C., Yaari, A., Singh, A., Subramaniam, V., Rosenfarb, D., Misra, P., Madsen, J., Stone, S., Kreiman, G., Katz, B., Cases, I., & Barbu, A. (2024). Brain treebank: Large-scale intracranial recordings from naturalistic language stimuli. NeurIPS. https://drive.google.com/file/d/1EeH0El2umcbRAYnKymI-X34KjssfJiGR/view?usp=sharing