[97] Michal Rolinek et al. "Variational autoencoders pursue PCA directions (by accident)". In: Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition. 2019, pp. 12406-12415. URL: https://openaccess.thecvf.com/content_CVPR_2019/html/Rolinek_Variational_Autoencoders_Pursue_PCA_Directions_by_Accident_CVPR_2019_paper.html.
[98] Sjoerd van Steenkiste et al. "Are Disentangled Representations Helpful for Abstract Visual Reasoning?" In: Advances in Neural Information Processing Systems. Vol. 32. Curran Associates, Inc., 2019. URL: https://papers.nips.cc/paper_files/paper/2019/bitstream/bc3c4a6331a8a9950945a1aa8c95ab8a-Abstract.html.
[99] Andrea Dittadi et al. "On the Transfer of Disentangled Representations in Realistic Settings". In: International Conference on Learning Representations. 2021. URL: https://openreview.net/forum?id=8VXvj1QNR11.
[100] W Jeffrey Johnston and Stefano Fusi. "Abstract representations emerge naturally in neural networks trained to perform multiple tasks". In: Nature Communications 14.1 (2023), p. 1040. DOI: 10.1038/s41467-023-36583-0.
[101] Marc-André Carbonneau et al. “Measuring disentanglement: A review of metrics”. In: IEEE Transactions on Neural Networks and Learning Systems (2022). DOI: 10.1109/TNNLS.2022.3218982.
[102] Cian Eastwood et al. "DCI-ES: An Extended Disentanglement Framework with Connections to Identifiability". In: The Eleventh International Conference on Learning Representations. 2023. URL: https://openreview.net/forum?id=462z-gLgSht.
[103] Yuwei Cui et al. "Diverse suppressive influences in area MT and selectivity to complex motion features". In: Journal of Neuroscience 33.42 (2013), pp. 16715-16728. DOI: 10.1523/JNEUROSCI.0203-13.2013.
[104] Yuwei Cui et al. "Inferring cortical variability from local field potentials". In: Journal of Neuroscience 36.14 (2016), pp. 4121-4135. DOI: 10.1523/JNEUROSCI.2502-15.2016.
[105] Maneesh Sahani and Jennifer Linden. "How Linear are Auditory Cortical Responses?" In: Advances in Neural Information Processing Systems. Vol. 15. MIT Press, 2002. URL: https : / / papers . nips . cc / paper _ files / paper / 2002 / hash / 7b4773c039d539af17c883eb9283dd14- Abstract.html.
[106] Patrick J Mineault et al. "Hierarchical processing of complex motion along the primate dorsal visual pathway". In: Proceedings of the National Academy of Sciences 109.16 (2012), E972-E980. DOI: 10.1073/pnas.1115685109.
[107] Eero P. Simoncelli and Bruno A. Olshausen. "Natural image statistics and neural representation." In: Annual Review of Neuroscience 24 (2001), pp. 1193-216. DOI: 10.1146/annurev.neuro.24.1.1193.
[108] Aaron van den Oord et al. “Representation Learning with Contrastive Predictive Coding”. In: (2019). arXiv: 1807.03748 [cs.LG].
[109] Karl S Muller et al. "Retinal motion statistics during natural locomotion". In: eLife 12 (2023), e82410. DOI: 10.7554/eLife.82410.
[110] Benedict Wild and Stefan Treue. "Primate extrastriate cortical area MST: a gateway between sensation and cognition". In: Journal of Neurophysiology 125.5 (2021), pp. 1851-1882. DOI: 10.1152/jn.00384.2020.
[111] Benedict Wild et al. "Electrophysiological dataset from macaque visual cortical area MST in response to a novel motion stimulus". In: Scientific Data 9 (2022). DOI: 10.1038/s41597-022-01239-z.
[112] Alex H Williams et al. "Generalized Shape Metrics on Neural Representations". In: Advances in Neural Information Processing Systems. Vol. 34. Curran Associates, Inc., 2021. URL: https://papers.nips.cc/paper_files/paper/2021/bitstream/252a3dbaeb32e7690242ad3b556e626b-Abstract.html.
[113] Lyndon Duong et al. "Representational Dissimilarity Metric Spaces for Stochastic Neural Networks". In: The Eleventh International Conference on Learning Representations. 2023. URL: https://openreview.net/forum?id=xjb563TH-GH.
[114] Max Klabunde et al. "Similarity of Neural Network Models: A Survey of Functional and Representational Measures". In: (2023). arXiv: 2305.06329 [cs.LG].