A comparative biology approach to DNN modeling of vision: A focus on differences, not similarities B Lonnqvist, A Bornet, A Doerig, MH Herzog Journal of vision 21 (10), 17-17, 2021 | 15 | 2021 |
Crowding in humans is unlike that in convolutional neural networks B Lonnqvist, ADF Clarke, R Chakravarthi Neural Networks 126, 262-274, 2020 | 12 | 2020 |
Modeling individual variation in visual search with reinforcement learning B Lonnqvist, M Elsner, AR Hunt, A Clarke PsyArXiv, 2020 | 2 | 2020 |
Latent Noise Segmentation: How Neural Noise Leads to the Emergence of Segmentation and Grouping B Lonnqvist, Z Wu, MH Herzog International Conference on Machine Learning (ICML 2024), 2024 | 1 | 2024 |
Current DNNs are Unable to Integrate Visual Information Across Object Discontinuities B Lonnqvist, E Scialom, Z Merchant, MH Herzog, M Schrimpf Cognitive Computational Neuroscience (CCN 2024), 2024 | | 2024 |
Perceptual Grouping with Latent Noise B Lonnqvist, Z Wu, MH Herzog | | 2024 |
A comment on Guo et al. (2022) B Lonnqvist, H Machiraju, MH Herzog arXiv preprint arXiv:2208.01456, 2022 | | 2022 |
Global information processing in feedforward deep networks B Lonnqvist, A Bornet, A Doerig, L Schmittwilken, MH Herzog Oral at the 22nd Annual Meeting of the Vision Sciences Society (VSS 2022), 2022 | | 2022 |