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Abstract

Let’s compete—benchmarking models in neuroscience: Computational modeling has become increasingly popular in neuroscience but it often lacks a common strategy for model comparison. Following the benchmarking approach ubiquitous in machine learning I will present three problems in neuroscience for which model comparison plays an important role: (1) Predicting where people look, (2) predicting when neurons spike, and (3) generative modeling of natural images. I will conclude with a discussion on the growing importance of Machine Learning in neuroscience and how the increasing proficiency of artificial neural networks in solving perceptual tasks opens exciting new opportunities for interaction between the two fields.