Beitrag zur experimentellen Parameteridentifikation linearer mechanischer Systeme mittels Modalanalyse. - Jörg Lücke (1984)

Hilberticus - A Tool Deciding an Elementary Sublanguage of Set Theory. - Jörg Lücke (IJCAR, 2001)

Macrocolumns as Decision Units. - Jörg Lücke; Christoph von der Malsburg; Rolf P. Würtz (ICANN, 2002)

Clustering with minicolumnar receptive field self-organization. - Jörg Lücke (IJCNN, 2004)

Rapid Processing and Unsupervised Learning in a Model of the Cortical Macrocolumn. - Jörg Lücke; Christoph von der Malsburg (Neural Comput., 2004)

Hierarchical self-organization of minicolumnar receptive fields. - Jörg Lücke (Neural Networks, 2004)

Dynamics of Cortical Columns - Sensitive Decision Making. - Jörg Lücke (ICANN (1), 2005)

Dynamics of Cortical Columns - Self-organization of Receptive Fields. - Jörg Lücke; Jan D. Bouecke (ICANN (1), 2005)

Rapid Correspondence Finding in Networks of Cortical Columns. - Jörg Lücke; Christoph von der Malsburg (ICANN (1), 2006)

A Dynamical Model for Receptive Field Self-organization in V1 Cortical Columns. - Jörg Lücke (ICANN (2), 2007)

Generalized Softmax Networks for Non-linear Component Extraction. - Jörg Lücke; Maneesh Sahani (ICANN (1), 2007)

Glial cells for information routing? - Caroline Möller; Jörg Lücke; Junmei Zhu; Pedro M. Faustmann; Christoph von der Malsburg (Cogn. Syst. Res., 2007)

Learning of Neural Information Routing for Correspondence Finding. - Jan D. Bouecke; Jörg Lücke (ICANN (2), 2008)

Invariant Face Recognitionin a Network of Cortical Columns. - Philipp Wolfrum; Jörg Lücke; Christoph von der Malsburg (VISAPP (2), 2008)

Maximal Causes for Non-linear Component Extraction. - Jörg Lücke; Maneesh Sahani (J. Mach. Learn. Res., 2008)

Rapid Convergence to Feature Layer Correspondences. - Jörg Lücke; Christian Keck; Christoph von der Malsburg (Neural Comput., 2008)

Occlusive Components Analysis. - Jörg Lücke; Richard E. Turner; Maneesh Sahani; Marc Henniges (NIPS, 2009)

Receptive Field Self-Organization in a Model of the Fine Structure in V1 Cortical Columns. - Jörg Lücke (Neural Comput., 2009)

Binary Sparse Coding. - Marc Henniges; Gervasio Puertas; Jörg Bornschein; Julian Eggert; Jörg Lücke (LVA/ICA, 2010)

Learning of Lateral Connections for Representational Invariant Recognition. - Christian Keck; Jörg Lücke (ICANN (3), 2010)

The Maximal Causes of Natural Scenes are Edge Filters. - Gervasio Puertas; Jörg Bornschein; Jörg Lücke (NIPS, 2010)

Expectation Truncation and the Benefits of Preselection In Training Generative Models. - Jörg Lücke; Julian Eggert (J. Mach. Learn. Res., 2010)

Select and Sample - A Model of Efficient Neural Inference and Learning. - Jacquelyn A. Shelton; Jörg Bornschein; Abdul-Saboor Sheikh; Pietro Berkes; Jörg Lücke (NIPS, 2011)

Unsupervised learning of translation invariant occlusive components. - Zhenwen Dai; Jörg Lücke (CVPR, 2012)

Autonomous cleaning of corrupted scanned documents - A generative modeling approach. - Zhenwen Dai; Jörg Lücke (CVPR, 2012)

Ternary Sparse Coding. - Georgios Exarchakis; Marc Henniges; Julian Eggert; Jörg Lücke (LVA/ICA, 2012)

Closed-Form EM for Sparse Coding and Its Application to Source Separation. - Jörg Lücke; Abdul-Saboor Sheikh (LVA/ICA, 2012)

Why MCA? Nonlinear sparse coding with spike-and-slab prior for neurally plausible image encoding. - Jacquelyn A. Shelton; Philip Sterne; Jörg Bornschein; Abdul-Saboor Sheikh; Jörg Lücke (NIPS, 2012)

Closed-Form Entropy Limits - A Tool to Monitor Likelihood Optimization of Probabilistic Generative Models. - Jörg Lücke; Marc Henniges (AISTATS, 2012)

Feedforward Inhibition and Synaptic Scaling - Two Sides of the Same Coin? - Christian Keck; Cristina Savin; Jörg Lücke (PLoS Comput. Biol., 2012)

What Are the Invariant Occlusive Components of Image Patches? A Probabilistic Generative Approach. - Zhenwen Dai; Georgios Exarchakis; Jörg Lücke (NIPS, 2013)

Are V1 Simple Cells Optimized for Visual Occlusions? A Comparative Study. - Jörg Bornschein; Marc Henniges; Jörg Lücke (PLoS Comput. Biol., 2013)

Efficient occlusive components analysis. - Marc Henniges; Richard E. Turner; Maneesh Sahani; Julian Eggert; Jörg Lücke (J. Mach. Learn. Res., 2014)

A truncated EM approach for spike-and-slab sparse coding. - Abdul-Saboor Sheikh; Jacquelyn A. Shelton; Jörg Lücke (J. Mach. Learn. Res., 2014)

Autonomous Document Cleaning - A Generative Approach to Reconstruct Strongly Corrupted Scanned Texts. - Zhenwen Dai; Jörg Lücke (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

Neural Simpletrons - Minimalistic Probabilistic Networks for Learning With Few Labels. - Dennis Forster; Abdul-Saboor Sheikh; Jörg Lücke (CoRR, 2015)

Beyond Manual Tuning of Hyperparameters. - Frank Hutter; Jörg Lücke; Lars Schmidt-Thieme (Künstliche Intell., 2015)

Speaker tracking for hearing aids. - Joachim Thiemann; Jörg Lücke; Steven van de Par (MLSP, 2016)

Neurons Equipped with Intrinsic Plasticity Learn Stimulus Intensity Statistics. - Travis Monk; Cristina Savin; Jörg Lücke (NIPS, 2016)

Select-and-Sample for Spike-and-Slab Sparse Coding. - Abdul-Saboor Sheikh; Jörg Lücke (NIPS, 2016)

Truncated variational EM for semi-supervised neural simpletrons. - Dennis Forster; Jörg Lücke (IJCNN, 2017)

Probabilistic and unsupervised machine learning for auditory data and pattern recognition. - Jörg Lücke (SPA, 2017)

Models of Acetylcholine and Dopamine Signals Differentially Improve Neural Representations. - Raphaël Holca-Lamarre; Jörg Lücke; Klaus Obermayer (Frontiers Comput. Neurosci., 2017)

Discrete Sparse Coding. - Georgios Exarchakis; Jörg Lücke (Neural Comput., 2017)

GP-Select: Accelerating EM Using Adaptive Subspace Preselection. - Jacquelyn A. Shelton; Jan Gasthaus; Zhenwen Dai; Jörg Lücke; Arthur Gretton (Neural Comput., 2017)

Binary Non-Negative Matrix Deconvolution for Audio Dictionary Learning. - Szymon Drgas; Tuomas Virtanen; Jörg Lücke; Antti Hurmalainen (IEEE ACM Trans. Audio Speech Lang. Process., 2017)

Can clustering scale sublinearly with its clusters? A variational EM acceleration of GMMs and k-means. - Dennis Forster; Jörg Lücke (AISTATS, 2018)

Evolutionary expectation maximization. - Enrico Guiraud; Jakob Drefs; Jörg Lücke (GECCO, 2018)

Truncated Variational Sampling for 'Black Box' Optimization of Generative Models. - Jörg Lücke; Zhenwen Dai; Georgios Exarchakis (LVA/ICA, 2018)

Accelerated Training of Large-Scale Gaussian Mixtures by a Merger of Sublinear Approaches. - Florian Hirschberger; Dennis Forster; Jörg Lücke (CoRR, 2018)

Neural Simpletrons: Learning in the Limit of Few Labels with Directed Generative Networks. - Dennis Forster; Abdul-Saboor Sheikh; Jörg Lücke (Neural Comput., 2018)

ProSper - A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions. - Georgios Exarchakis; Jörg Bornschein; Abdul-Saboor Sheikh; Zhenwen Dai; Marc Henniges; Jakob Drefs; Jörg Lücke (CoRR, 2019)

STRFs in primary auditory cortex emerge from masking-based statistics of natural sounds. - Abdul-Saboor Sheikh; Nicol S. Harper; Jakob Drefs; Yosef Singer; Zhenwen Dai; Richard E. Turner; Jörg Lücke (PLoS Comput. Biol., 2019)

k-means as a variational EM approximation of Gaussian mixture models. - Jörg Lücke; Dennis Forster (Pattern Recognit. Lett., 2019)

A Double-Dictionary Approach Learns Component Means and Variances for V1 Encoding. - S. Hamid Mousavi; Jakob Drefs; Jörg Lücke (LOD (2), 2020)

Maximal Causes for Exponential Family Observables. - S. Hamid Mousavi; Jakob Drefs; Florian Hirschberger; Jörg Lücke (CoRR, 2020)

The Evidence Lower Bound of Variational Autoencoders Converges to a Sum of Three Entropies. - Jörg Lücke; Dennis Forster; Zhenwen Dai (CoRR, 2020)

Direct Evolutionary Optimization of Variational Autoencoders With Binary Latents. - Enrico Guiraud; Jakob Drefs; Jörg Lücke (CoRR, 2020)

Inference and Learning in a Latent Variable Model for Beta Distributed Interval Data. - S. Hamid Mousavi; Mareike Buhl; Enrico Guiraud; Jakob Drefs; Jörg Lücke (Entropy, 2021)

Generalizable dimensions of human cortical auditory processing of speech in natural soundscapes: A data-driven ultra high field fMRI approach. - Moritz Boos; Jörg Lücke; Jochem W. Rieger (NeuroImage, 2021)

Direct Evolutionary Optimization of Variational Autoencoders with Binary Latents. - Jakob Drefs; Enrico Guiraud; Filippos Panagiotou; Jörg Lücke (ECML/PKDD (3), 2022)

On the Convergence of the ELBO to Entropy Sums. - Jörg Lücke (CoRR, 2022)

Evolutionary Variational Optimization of Generative Models. - Jakob Drefs; Enrico Guiraud; Jörg Lücke (J. Mach. Learn. Res., 2022)

A Variational EM Acceleration for Efficient Clustering at Very Large Scales. - Florian Hirschberger; Dennis Forster; Jörg Lücke (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

The ELBO of Variational Autoencoders Converges to a Sum of Entropies. - Simon Damm; Dennis Forster; Dmytro Velychko; Zhenwen Dai; Asja Fischer; Jörg Lücke (AISTATS, 2023)

Generic Unsupervised Optimization for a Latent Variable Model With Exponential Family Observables. - S. Hamid Mousavi; Jakob Drefs; Florian Hirschberger; Jörg Lücke (J. Mach. Learn. Res., 2023)

Learning Sparse Codes with Entropy-Based ELBOs. - Dmytro Velychko; Simon Damm; Asja Fischer; Jörg Lücke (AISTATS, 2024)

Blind Zero-Shot Audio Restoration: A Variational Autoencoder Approach for Denoising and Inpainting. - Veranika Boukun; Jakob Drefs; Jörg Lücke (INTERSPEECH, 2024)

Zero-shot denoising of microscopy images recorded at high-resolution limits. - Sebastian Salwig; Jakob Drefs; Jörg Lücke (PLoS Comput. Biol., 2024)

Towards multidimensional attentive voice tracking - estimating voice state from auditory glimpses with regression neural networks and Monte Carlo sampling. - Joanna Luberadzka; Hendrik Kayser; Jörg Lücke; Volker Hohmann (EURASIP J. Audio Speech Music. Process., 2024)

Generative Models with ELBOs Converging to Entropy Sums. - Jan Warnken; Dmytro Velychko; Simon Damm; Asja Fischer; Jörg Lücke (CoRR, 2025)

Sublinear Variational Optimization of Gaussian Mixture Models with Millions to Billions of Parameters. - Sebastian Salwig; Till Kahlke; Florian Hirschberger; Dennis Forster; Jörg Lücke (CoRR, 2025)

Linear and Nonlinear Generative Models for 'Zero-Shot' Image Denoising in the Limit of Few Photons. - S. Hamid Mousavi; Jörg Lücke (J. Math. Imaging Vis., 2025)