Jakob H. Macke
According to our database^{1},
Jakob H. Macke
authored at least 31 papers
between 2006 and 2019.
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at ei.tum.de
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Bibliography
2019
Inference of a mesoscopic population model from population spike trains.
CoRR, 2019
Teaching deep neural networks to localize sources in superresolution microscopy by combining simulationbased learning and unsupervised learning.
CoRR, 2019
Intrinsic dimension of data representations in deep neural networks.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019
Automatic Posterior Transformation for LikelihoodFree Inference.
Proceedings of the 36th International Conference on Machine Learning, 2019
2018
Communitybased benchmarking improves spike rate inference from twophoton calcium imaging data.
PLoS Computational Biology, 2018
Analyzing biological and artificial neural networks: challenges with opportunities for synergy?
CoRR, 2018
Likelihoodfree inference with emulator networks.
Proceedings of the Symposium on Advances in Approximate Bayesian Inference, 2018
2017
Signatures of criticality arise from random subsampling in simple population models.
PLoS Computational Biology, 2017
Fast amortized inference of neural activity from calcium imaging data with variational autoencoders.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Extracting lowdimensional dynamics from multiple largescale neural population recordings by learning to predict correlations.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
Flexible statistical inference for mechanistic models of neural dynamics.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017
2015
Unlocking neural population nonstationarities using hierarchical dynamics models.
Proceedings of the Advances in Neural Information Processing Systems 28: Annual Conference on Neural Information Processing Systems 2015, 2015
2014
Electrophysiology Analysis, Bayesian.
Proceedings of the Encyclopedia of Computational Neuroscience, 2014
A Bayesian model for identifying hierarchically organised states in neural population activity.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
Lowdimensional models of neural population activity in sensory cortical circuits.
Proceedings of the Advances in Neural Information Processing Systems 27: Annual Conference on Neural Information Processing Systems 2014, 2014
2013
Estimation Bias in Maximum Entropy Models.
Entropy, 2013
Inferring neural population dynamics from multiple partial recordings of the same neural circuit.
Proceedings of the Advances in Neural Information Processing Systems 26: 27th Annual Conference on Neural Information Processing Systems 2013. Proceedings of a meeting held December 58, 2013
2012
Spectral learning of linear dynamics from generalisedlinear observations with application to neural population data.
Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 36, 2012
2011
Gaussian process methods for estimating cortical maps.
NeuroImage, 2011
Statistical Analysis of MultiCell Recordings: Linking Population Coding Models to Experimental Data.
Frontiers Comput. Neurosci., 2011
How biased are maximum entropy models?
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 1214 December 2011, 2011
Empirical models of spiking in neural populations.
Proceedings of the Advances in Neural Information Processing Systems 24: 25th Annual Conference on Neural Information Processing Systems 2011. Proceedings of a meeting held 1214 December 2011, 2011
2010
Modeling Population Spike Trains with Specified TimeVarying Spike Rates, TrialtoTrial Variability, and Pairwise Signal and Noise Correlations.
Frontiers Comput. Neurosci., 2010
Bayesian inference for generalized linear models for spiking neurons.
Frontiers Comput. Neurosci., 2010
2009
Generating Spike Trains with Specified Correlation Coefficients.
Neural Computation, 2009
Bayesian population decoding of spiking neurons.
Frontiers Comput. Neurosci., 2009
Bayesian estimation of orientation preference maps.
Proceedings of the Advances in Neural Information Processing Systems 22: 23rd Annual Conference on Neural Information Processing Systems 2009. Proceedings of a meeting held 710 December 2009, 2009
2007
Receptive Fields without SpikeTriggering.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007
Bayesian Inference for Spiking Neuron Models with a Sparsity Prior.
Proceedings of the Advances in Neural Information Processing Systems 20, 2007
Unsupervised learning of a steerable basis for invariant image representations.
Proceedings of the Human Vision and Electronic Imaging XII, San Jose, CA, USA, January 29, 2007
2006
Inducing Metric Violations in Human Similarity Judgements.
Proceedings of the Advances in Neural Information Processing Systems 19, 2006