Xavier Boix

BCS

grad student

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Jang H, Zaidi SSA, Boix X, et al. (2023) Robustness to Transformations Across Categories: Is Robustness Driven by Invariant Neural Representations? Neural Computation. 1-28
Sundaram S, Sinha D, Groth M, et al. (2022) Recurrent connections facilitate symmetry perception in deep networks. Scientific Reports. 12: 20931
Sakai A, Sunagawa T, Madan S, et al. (2022) Three approaches to facilitate invariant neurons and generalization to out-of-distribution orientations and illuminations. Neural Networks : the Official Journal of the International Neural Network Society. 155: 119-143
D'Amario V, Srivastava S, Sasaki T, et al. (2022) The Data Efficiency of Deep Learning Is Degraded by Unnecessary Input Dimensions. Frontiers in Computational Neuroscience. 16: 760085
Villalobos K, Štih V, Ahmadinejad A, et al. (2021) Do Neural Networks for Segmentation Understand Insideness? Neural Computation. 33: 2511-2549
Vinken K, Boix X, Kreiman G. (2020) Incorporating intrinsic suppression in deep neural networks captures dynamics of adaptation in neurophysiology and perception. Science Advances. 6
Roig G, Chen F, Boix X, et al. (2017) Eccentricity Dependent Deep Neural Networks for Modeling Human Vision Journal of Vision. 17: 808-808