Publikationen von M Bethge

Bethge, M.: Factorial coding of natural images: How effective are linear filters in removing higher-order dependencies? In 7th Conference of Tuebingen Junior Neuroscientists (NeNa 2006), S. 17. 7th Conference of Tuebingen Junior Neuroscientists (NeNa 2006), Oberjoch, Germany, 26. November 2006 - 28. November 2006. (2006)

Gerwinn, S.; Seeger, M.; Zeck, G.; Bethge, M.: Bayesian Neural System identification: error bars, receptive fields and neural couplings. In 7th Conference of Tuebingen Junior Neuroscientists (NeNa 2006), S. 9. 7th Conference of Tuebingen Junior Neuroscientists (NeNa 2006), Oberjoch, Germany, 26. November 2006 - 28. November 2006. (2006)

Higgins, I.; Konkle, T.; Bethge, M.: What sorts of cognitive or biological (architectural) inductive biases will be crucial for developing effective artificial intelligence? NeurIPS 2019 Workshop: Shared Visual Representations in Human and Machine Intelligence, Vancouver, BC, Canada (2019)

Bethge, M.: Wie Maschinen lernen: Deep Learning. HumanIThesia-Kongress „Ethik und KI“ 2017, Tübingen, Germany (2017)

Bethge, M.: When will signatures of criticality provide critical insights about neural computations? Excellence Workshop "Dynamical Network States, Criticality and Cortical Function", Delmenhorst, Germany (2017)

Bethge, M.: Understanding Complex Neural Network Computations. AREADNE 2016: Research in Encoding And Decoding of Neural Ensembles, Santorini, Greece (2016)

Bethge, M.: Let's compete: Benchmarking models in neuroscience. NIPS 2015 Workshop on Statistical Methods for Understanding Neural Systems, Montréal, Canada (2015)

Bethge, M.: Perceiving Neural Networks. Max Planck ETH Center for Learning Systems Inauguration, Tübingen, Germany (2015)

Bethge, M.: Understanding biological and artificial neural networks. 5th Bernstein Sparks Workshop: Neural models of decision making in natural inference tasks - from theory to experiment, Tübingen, Germany (2015)

Bethge, M.: Natural image statistics neural representation learning. Autonomous Learning: Summer School 2014, Leipzig, Germany (2014)

Bethge, M.: Normative models and identification of nonlinear neural representations. Institut d'Etudes de la Cognition (IEC) at the Ecole Normale Supérieure: Group for Neural Theory, Paris, France (2013)

Bethge, M.: Beyond GLMs: A generative mixture modeling approach to neural system identification. Columbia University: Workshop on Quantifying Structure in Large Neural Datasets, New York, NY, USA (2013)

Bethge, M.: The unsolved mystery of neural information processing: taming the curse of dimensionality. Osnabrück Computational Cognition Alliance Meeting on "The Brain as an Information Processing System" (OCCAM 2012), Osnabrück, Germany (2012)

Bethge, M.: Natural image statistics, 85% explained. City University of New York: Initiative for the Theoretical Sciences, New York, NY, USA (2012)

Bethge, M.: An analytically tractable model of neural population activity in the presence of common input explains high-order correlations and entropy. CIN Systems Neuroscience Retreat, Reutlingen, Germany (2010)

Bethge, M.: How Much More Does V1 Know About the Statistics of Natural Images Than the Retina? Workshop on Machine Learning: Approaches to Representational Learning and Recognition in Vision, Frankfurt a.M., Germany (2008)

Macke, J.; Opper, M.; Bethge, M.: How pairwise correlations aect the redundancy in large populations of neurons. Bernstein Symposium 2008, München, Germany (2008)

Bethge, M.: Hoch much can bandpass filtering, orientation selectivity, and divisive normalization contribute to the reduction of redundancy in natural images? International Workshop: Aspects of Adaptive Cortex Dynamics, Delmenhorst, Germany (2008)

Bethge, M.: Sensory coding of natural images: bandpass filtering, orientation selectivity and contrast gain control. Gordon Research Conference: Sensory Coding & The Natural Environment 2008, Lucca, Italy (2008)

Bethge, M.: Bayesian Inference of Neural Population Codes with a Sparsity Prior. Bernstein Center for Computational Neuroscience: Bernstein Colloquium, München, Germany (2007)