Showing 1–17 of 17 results
/ Date/ Name
Feb 6, 2024A comparison between humans and AI at recognizing objects in unusual posesDec 16, 2024On the Ability of Deep Networks to Learn Symmetries from Data: A Neural Kernel TheoryJan 3, 2019A Unified Theory of Early Visual Representations from Retina to Cortex through Anatomically Constrained Deep CNNsMay 27, 2023On the special role of class-selective neurons in early trainingFeb 5, 2024ViewFusion: Learning Composable Diffusion Models for Novel View SynthesisDec 15, 2025A Deep Learning Model of Mental Rotation Informed by Interactive VR ExperimentsFeb 20, 2026Latent Equivariant Operators for Robust Object Recognition: Promises and ChallengesFeb 3, 2023Blockwise Self-Supervised Learning at ScaleNov 16, 2018Optogenetic vision restoration with high resolutionFeb 10, 2021Addressing the Topological Defects of Disentanglement via Distributed OperatorsJan 4, 2018A simple model for low variability in neural spike trainsJan 5, 2018Separating intrinsic interactions from extrinsic correlations in a network of sensory neuronsOct 24, 2014Dynamical criticality in the collective activity of a population of retinal neuronsJul 16, 2022Progress and limitations of deep networks to recognize objects in unusual posesApr 9, 2019Predicting synchronous firing of large neural populations from sequential recordingsMar 4, 2021Barlow Twins: Self-Supervised Learning via Redundancy ReductionMay 11, 2016Nonlinear decoding of a complex movie from the mammalian retina