Lakshminarasimhan K, Petsalis M, Park H, DeAngelis G, Pitkow X (2017). A Dynamic Bayesian Observer Model Reveals Origins of Bias in Visual Path Integration. bioRXiv: 10.1101/191817. [pdf]
Orhan AE, Pitkow X (2018). Skip connections eliminate singularities. International Conference on Learning Representations [pdf]. (top 3%)
Lakshminarasimhan K, Pouget A, DeAngelis GCAngelaki DE*Pitkow X* (2017). Inferring decoding strategies for multiple correlated neural populations. bioRXiv: 108019. (in review)
Pitkow X, Angelaki D (2017). Inference in the brain: Statistics flowing in redundant population codes. Neuron. 94(5): 943–53. [pdf]
Pitkow X (2016). Probability by timeNeuron. 92(2): 275–277 [pdf]. Preview of Orbán G, Berkes P, Fiser J, Lengyel M (2016). Neural variability and sampling-based probabilistic representations in the visual cortex. Neuron. 92(2): 530–543. tigerthumbnail
Kim HG, Pitkow X, Angelaki D, DeAngelis G (2016). A simple approach to ignoring irrelevant variables by population decoding based on multisensory neuronsJournal of Neurophysiology. 116(3): 1449–67. doi: 10.1152/jn.00005.2016 [link].
Raju RV, Pitkow X (2016). Inference by reparameterization in neural population codes. Advances in Neural Information Processing Systems [pdf]
Pitkow X, Liu S, Angelaki D, DeAngelis GD, Pouget A (2015). How can single sensory neurons predict behavior? Neuron 87(2): 411–423. doi:10.1016/j.neuron.2015.06.033 [pdf] JointlyBadNoise
Moreno-Bote R, Beck J, Kanitscheider I, Pitkow X, Latham P, Pouget A (2014). Information-limiting correlationsNature Neuroscience 17: 1410–1417. doi:10.1038/nn.3807 [pdf] BadNoiseManifold8
Beck J, Ma WJ, Pitkow X, Latham P, Pouget A (2012). Not noisy, just wrong: the role of suboptimal inference in behavioral variabilityNeuron 74(1): 30–39. doi: 10.1016/j.neuron.2012.03.016 [pdf] SuboptimalFraction
Pitkow X, Meister M (2012). Decorrelation and efficient coding by retinal ganglion cells. Nature Neuroscience 15: 628–35. doi: 10.1038/nn.3064 [pdf]  Sphere1_biggrey_crop
Pitkow X (2012). Compressive neural representation of sparse, high-dimensional probabilitiesAdvances in Neural Information Processing Systems. [pdf] [4-min video] /private/tmp/
Pitkow X, Ahmadian Y, Miller DK (2011). Learning unbelievable probabilities. Advances in Neural Information Processing Systems. [pdf] Fig1_v12_Bethe
Pitkow X (2010). Exact feature probabilities in images with occlusion. Journal of Vision 10(14): 42. [pdf]  DeadLeavesHighContrast
Pitkow X, Sompolinsky H, Meister M (2007). A neural computation for visual acuity in the presence of eye movements. PLoS Biology 5(12): e331. [pdf]  EyeMovementsThumbnail

Book chapters

Pitkow X, Meister M (2014). Neural computation in sensory systems. In: The Cognitive Neurosciences V. Gazzaniga MS & Mangun GR eds., MIT Press.

Pitkow X (2011). What is an image? In Elkins J, Naef M (eds.) What Is an Image? (160–161). Penn State University Press.