Showing 1–14 of 14 results
/ Date/ Name
Jul 3, 2014The Hamiltonian brain: efficient probabilistic inference with excitatory-inhibitory neural circuit dynamicsJun 3, 2017Asymptotic scaling properties of the posterior mean and variance in the Gaussian scale mixture modelDec 24, 2011Bayesian Active Learning for Classification and Preference LearningJan 28, 2013How (not) to assess the importance of correlations for the matching of spontaneous and evoked activityOct 10, 2016Characterizing variability in nonlinear recurrent neuronal networksMay 13, 2003Properties of a random attachment growing networkApr 14, 2014Fast sampling for Bayesian inference in neural circuitsFeb 10, 2015On the role of time in perceptual decision makingJul 14, 2025Dynamical stability for dense patterns in discrete attractor neural networksFeb 13, 2026Hierarchical Successor Representation for Robust TransferJul 24, 2018Sampling-based probabilistic inference emerges from learning in neural circuits with a cost on reliabilityDec 4, 2025Setting up for failure: automatic discovery of the neural mechanisms of cognitive errorsDec 17, 2025When sufficiency is insufficient: the functional information bottleneck for identifying probabilistic neural representationsMay 2, 2025A flexible Bayesian non-parametric mixture model reveals multiple dependencies of swap errors in visual working memory