| Brain-score: Which artificial neural network for object recognition is most brain-like? M Schrimpf, J Kubilius, H Hong, NJ Majaj, R Rajalingham, EB Issa, K Kar, ... BioRxiv, 407007, 2018 | 533 | 2018 |
| Evidence that recurrent circuits are critical to the ventral stream’s execution of core object recognition behavior K Kar, J Kubilius, K Schmidt, EB Issa, JJ DiCarlo Nature neuroscience 22 (6), 974-983, 2019 | 469 | 2019 |
| Deep neural networks as a computational model for human shape sensitivity J Kubilius, S Bracci, HP Op de Beeck PLoS computational biology 12 (4), e1004896, 2016 | 324 | 2016 |
| Threedworld: A platform for interactive multi-modal physical simulation C Gan, J Schwartz, S Alter, D Mrowca, M Schrimpf, J Traer, J De Freitas, ... arXiv preprint arXiv:2007.04954, 2020 | 277 | 2020 |
| Brain-like object recognition with high-performing shallow recurrent ANNs J Kubilius, M Schrimpf, K Kar, R Rajalingham, H Hong, N Majaj, E Issa, ... Advances in neural information processing systems 32, 2019 | 274 | 2019 |
| Integrative benchmarking to advance neurally mechanistic models of human intelligence M Schrimpf, J Kubilius, MJ Lee, NAR Murty, R Ajemian, JJ DiCarlo Neuron 108 (3), 413-423, 2020 | 226 | 2020 |
| Mirror-image sensitivity and invariance in object and scene processing pathways DD Dilks, JB Julian, J Kubilius, ES Spelke, N Kanwisher Journal of Neuroscience 31 (31), 11305-11312, 2011 | 176 | 2011 |
| Task-driven convolutional recurrent models of the visual system A Nayebi, D Bear, J Kubilius, K Kar, S Ganguli, D Sussillo, JJ DiCarlo, ... Advances in neural information processing systems 31, 2018 | 172 | 2018 |
| Cornet: Modeling the neural mechanisms of core object recognition J Kubilius, M Schrimpf, A Nayebi, D Bear, DLK Yamins, JJ DiCarlo BioRxiv, 408385, 2018 | 156 | 2018 |
| The occipital place area represents the local elements of scenes FS Kamps, JB Julian, J Kubilius, N Kanwisher, DD Dilks Neuroimage 132, 417-424, 2016 | 110 | 2016 |
| Bistable Gestalts reduce activity in the whole of V1, not just the retinotopically predicted parts LH de-Wit, J Kubilius, J Wagemans, HPO de Beeck Journal of Vision 12 (11), 12-12, 2012 | 86 | 2012 |
| Emergence of perceptual Gestalts in the human visual cortex: the case of the configural-superiority effect J Kubilius, J Wagemans, HP Op de Beeck Psychological science 22 (10), 1296-1303, 2011 | 79* | 2011 |
| Goal-driven recurrent neural network models of the ventral visual stream A Nayebi, J Sagastuy-Brena, DM Bear, K Kar, J Kubilius, S Ganguli, ... bioRxiv, 2021.02. 17.431717, 2021 | 50* | 2021 |
| A conceptual framework of computations in mid-level vision J Kubilius, J Wagemans, HP Op de Beeck Frontiers in computational neuroscience 8, 158, 2014 | 37 | 2014 |
| Toward goal-driven neural network models for the rodent whisker-trigeminal system C Zhuang, J Kubilius, MJ Hartmann, DL Yamins Advances in Neural Information Processing Systems 30, 2017 | 35 | 2017 |
| Brain-decoding fMRI reveals how wholes relate to the sum of parts J Kubilius, A Baeck, J Wagemans, HPO de Beeck Cortex 72, 5-14, 2015 | 30 | 2015 |
| A framework for streamlining research workflow in neuroscience and psychology J Kubilius Frontiers in neuroinformatics 7, 52, 2014 | 24 | 2014 |
| Measuring sample efficiency and generalization in reinforcement learning benchmarks: Neurips 2020 procgen benchmark S Mohanty, J Poonganam, A Gaidon, A Kolobov, B Wulfe, D Chakraborty, ... arXiv preprint arXiv:2103.15332, 2021 | 23 | 2021 |
| Cue-invariant shape recognition in rats as tested with second-order contours R De Keyser, C Bossens, J Kubilius, HPO de Beeck Journal of vision 15 (15), 14-14, 2015 | 23 | 2015 |
| Predict, then simplify J Kubilius NeuroImage 180, 110-111, 2018 | 13 | 2018 |
James J DiCarloMassachusetts Institute of Technology在 mit.edu 的电子邮件经过验证
