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ORCIDJörg Lücke
Person information
- affiliation: University of Oldenburg, Germany
- affiliation: University College London, UK
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Books and Theses
- 1984
[b1]Jörg Lücke:
Beitrag zur experimentellen Parameteridentifikation linearer mechanischer Systeme mittels Modalanalyse. Technische Hochschule Magdeburg, Germany, 1984
Journal Articles
- 2024
- [j26]Joanna Luberadzka
, Hendrik Kayser, Jörg Lücke, Volker Hohmann:
Towards multidimensional attentive voice tracking - estimating voice state from auditory glimpses with regression neural networks and Monte Carlo sampling. EURASIP J. Audio Speech Music. Process. 2024(1): 27 (2024) - 2023
- [j25]S. Hamid Mousavi, Jakob Drefs, Florian Hirschberger, Jörg Lücke:
Generic Unsupervised Optimization for a Latent Variable Model With Exponential Family Observables. J. Mach. Learn. Res. 24: 285:1-285:59 (2023) - 2022
- [j24]Jakob Drefs, Enrico Guiraud, Jörg Lücke:
Evolutionary Variational Optimization of Generative Models. J. Mach. Learn. Res. 23: 21:1-21:51 (2022) - [j23]Florian Hirschberger, Dennis Forster, Jörg Lücke:
A Variational EM Acceleration for Efficient Clustering at Very Large Scales. IEEE Trans. Pattern Anal. Mach. Intell. 44(12): 9787-9801 (2022) - 2021
- [j22]S. Hamid Mousavi, Mareike Buhl, Enrico Guiraud, Jakob Drefs, Jörg Lücke:
Inference and Learning in a Latent Variable Model for Beta Distributed Interval Data. Entropy 23(5): 552 (2021) - [j21]Moritz Boos, Jörg Lücke, Jochem W. Rieger:
Generalizable dimensions of human cortical auditory processing of speech in natural soundscapes: A data-driven ultra high field fMRI approach. NeuroImage 237: 118106 (2021) - 2019
- [j20]Abdul-Saboor Sheikh, Nicol S. Harper, Jakob Drefs, Yosef Singer, Zhenwen Dai, Richard E. Turner, Jörg Lücke:
STRFs in primary auditory cortex emerge from masking-based statistics of natural sounds. PLoS Comput. Biol. 15(1) (2019) - [j19]Jörg Lücke, Dennis Forster:
k-means as a variational EM approximation of Gaussian mixture models. Pattern Recognit. Lett. 125: 349-356 (2019) - 2018
- [j18]Dennis Forster, Abdul-Saboor Sheikh, Jörg Lücke:
Neural Simpletrons: Learning in the Limit of Few Labels with Directed Generative Networks. Neural Comput. 30(8) (2018) - 2017
- [j17]Raphaël Holca-Lamarre, Jörg Lücke, Klaus Obermayer:
Models of Acetylcholine and Dopamine Signals Differentially Improve Neural Representations. Frontiers Comput. Neurosci. 11: 54 (2017) - [j16]Jacquelyn A. Shelton, Jan Gasthaus, Zhenwen Dai, Jörg Lücke, Arthur Gretton:
GP-Select: Accelerating EM Using Adaptive Subspace Preselection. Neural Comput. 29(8): 2177-2202 (2017) - [j15]Georgios Exarchakis, Jörg Lücke:
Discrete Sparse Coding. Neural Comput. 29(11) (2017) - [j14]Szymon Drgas, Tuomas Virtanen, Jörg Lücke, Antti Hurmalainen:
Binary Non-Negative Matrix Deconvolution for Audio Dictionary Learning. IEEE ACM Trans. Audio Speech Lang. Process. 25(8): 1644-1656 (2017) - 2015
- [j13]Frank Hutter, Jörg Lücke, Lars Schmidt-Thieme:
Beyond Manual Tuning of Hyperparameters. Künstliche Intell. 29(4): 329-337 (2015) - 2014
- [j12]Abdul-Saboor Sheikh, Jacquelyn A. Shelton, Jörg Lücke:
A truncated EM approach for spike-and-slab sparse coding. J. Mach. Learn. Res. 15(1): 2653-2687 (2014) - [j11]Marc Henniges, Richard E. Turner, Maneesh Sahani, Julian Eggert, Jörg Lücke:
Efficient occlusive components analysis. J. Mach. Learn. Res. 15(1): 2689-2722 (2014) - [j10]Zhenwen Dai, Jörg Lücke:
Autonomous Document Cleaning - A Generative Approach to Reconstruct Strongly Corrupted Scanned Texts. IEEE Trans. Pattern Anal. Mach. Intell. 36(10): 1950-1962 (2014) - 2013
- [j9]Jörg Bornschein, Marc Henniges, Jörg Lücke:
Are V1 Simple Cells Optimized for Visual Occlusions? A Comparative Study. PLoS Comput. Biol. 9(6) (2013) - 2012
- [j8]Christian Keck, Cristina Savin, Jörg Lücke:
Feedforward Inhibition and Synaptic Scaling - Two Sides of the Same Coin? PLoS Comput. Biol. 8(3) (2012) - 2010
- [j7]Jörg Lücke, Julian Eggert:
Expectation Truncation and the Benefits of Preselection In Training Generative Models. J. Mach. Learn. Res. 11: 2855-2900 (2010) - 2009
- [j6]Jörg Lücke:
Receptive Field Self-Organization in a Model of the Fine Structure in V1 Cortical Columns. Neural Comput. 21(10): 2805-2845 (2009) - 2008
- [j5]Jörg Lücke, Maneesh Sahani:
Maximal Causes for Non-linear Component Extraction. J. Mach. Learn. Res. 9: 1227-1267 (2008) - [j4]Jörg Lücke, Christian Keck, Christoph von der Malsburg:
Rapid Convergence to Feature Layer Correspondences. Neural Comput. 20(10): 2441-2463 (2008) - 2007
- [j3]Caroline Möller, Jörg Lücke, Junmei Zhu, Pedro M. Faustmann, Christoph von der Malsburg:
Glial cells for information routing? Cogn. Syst. Res. 8(1): 28-35 (2007) - 2004
- [j2]Jörg Lücke, Christoph von der Malsburg:
Rapid Processing and Unsupervised Learning in a Model of the Cortical Macrocolumn. Neural Comput. 16(3): 501-533 (2004) - [j1]Jörg Lücke:
Hierarchical self-organization of minicolumnar receptive fields. Neural Networks 17(8-9): 1377-1389 (2004)
Conference and Workshop Papers
- 2024
- [c33]Dmytro Velychko, Simon Damm, Asja Fischer, Jörg Lücke:
Learning Sparse Codes with Entropy-Based ELBOs. AISTATS 2024: 2089-2097 - 2023
- [c32]Simon Damm, Dennis Forster, Dmytro Velychko, Zhenwen Dai, Asja Fischer, Jörg Lücke:
The ELBO of Variational Autoencoders Converges to a Sum of Entropies. AISTATS 2023: 3931-3960 - 2022
- [c31]Jakob Drefs, Enrico Guiraud, Filippos Panagiotou, Jörg Lücke:
Direct Evolutionary Optimization of Variational Autoencoders with Binary Latents. ECML/PKDD (3) 2022: 357-372 - 2020
- [c30]S. Hamid Mousavi, Jakob Drefs, Jörg Lücke:
A Double-Dictionary Approach Learns Component Means and Variances for V1 Encoding. LOD (2) 2020: 240-244 - 2018
- [c29]Dennis Forster, Jörg Lücke:
Can clustering scale sublinearly with its clusters? A variational EM acceleration of GMMs and k-means. AISTATS 2018: 124-132 - [c28]Enrico Guiraud, Jakob Drefs, Jörg Lücke:
Evolutionary expectation maximization. GECCO 2018: 442-449 - [c27]Jörg Lücke, Zhenwen Dai, Georgios Exarchakis:
Truncated Variational Sampling for 'Black Box' Optimization of Generative Models. LVA/ICA 2018: 467-478 - 2017
- [c26]Dennis Forster, Jörg Lücke:
Truncated variational EM for semi-supervised neural simpletrons. IJCNN 2017: 3769-3776 - [c25]Jörg Lücke:
Probabilistic and unsupervised machine learning for auditory data and pattern recognition. SPA 2017: 13 - 2016
- [c24]Joachim Thiemann, Jörg Lücke, Steven van de Par:
Speaker tracking for hearing aids. MLSP 2016: 1-6 - [c23]Abdul-Saboor Sheikh, Jörg Lücke:
Select-and-Sample for Spike-and-Slab Sparse Coding. NIPS 2016: 3927-3935 - [c22]Travis Monk, Cristina Savin, Jörg Lücke:
Neurons Equipped with Intrinsic Plasticity Learn Stimulus Intensity Statistics. NIPS 2016: 4278-4286 - 2013
- [c21]Zhenwen Dai, Georgios Exarchakis, Jörg Lücke:
What Are the Invariant Occlusive Components of Image Patches? A Probabilistic Generative Approach. NIPS 2013: 243-251 - 2012
- [c20]Zhenwen Dai, Jörg Lücke:
Unsupervised learning of translation invariant occlusive components. CVPR 2012: 2400-2407 - [c19]Zhenwen Dai, Jörg Lücke:
Autonomous cleaning of corrupted scanned documents - A generative modeling approach. CVPR 2012: 3338-3345 - [c18]Georgios Exarchakis, Marc Henniges, Julian Eggert, Jörg Lücke:
Ternary Sparse Coding. LVA/ICA 2012: 204-212 - [c17]Jörg Lücke, Abdul-Saboor Sheikh:
Closed-Form EM for Sparse Coding and Its Application to Source Separation. LVA/ICA 2012: 213-221 - [c16]Jacquelyn A. Shelton, Philip Sterne, Jörg Bornschein, Abdul-Saboor Sheikh, Jörg Lücke:
Why MCA? Nonlinear sparse coding with spike-and-slab prior for neurally plausible image encoding. NIPS 2012: 2285-2293 - [c15]Jörg Lücke, Marc Henniges:
Closed-Form Entropy Limits - A Tool to Monitor Likelihood Optimization of Probabilistic Generative Models. AISTATS 2012: 731-740 - 2011
- [c14]Jacquelyn A. Shelton, Jörg Bornschein, Abdul-Saboor Sheikh, Pietro Berkes, Jörg Lücke:
Select and Sample - A Model of Efficient Neural Inference and Learning. NIPS 2011: 2618-2626 - 2010
- [c13]Marc Henniges, Gervasio Puertas, Jörg Bornschein, Julian Eggert, Jörg Lücke:
Binary Sparse Coding. LVA/ICA 2010: 450-457 - [c12]Christian Keck, Jörg Lücke:
Learning of Lateral Connections for Representational Invariant Recognition. ICANN (3) 2010: 21-30 - [c11]Gervasio Puertas, Jörg Bornschein, Jörg Lücke:
The Maximal Causes of Natural Scenes are Edge Filters. NIPS 2010: 1939-1947 - 2009
- [c10]Jörg Lücke, Richard E. Turner, Maneesh Sahani, Marc Henniges:
Occlusive Components Analysis. NIPS 2009: 1069-1077 - 2008
- [c9]Jan D. Bouecke, Jörg Lücke:
Learning of Neural Information Routing for Correspondence Finding. ICANN (2) 2008: 557-566 - [c8]Philipp Wolfrum, Jörg Lücke, Christoph von der Malsburg:
Invariant Face Recognitionin a Network of Cortical Columns. VISAPP (2) 2008: 38-45 - 2007
- [c7]Jörg Lücke:
A Dynamical Model for Receptive Field Self-organization in V1 Cortical Columns. ICANN (2) 2007: 389-398 - [c6]Jörg Lücke, Maneesh Sahani:
Generalized Softmax Networks for Non-linear Component Extraction. ICANN (1) 2007: 657-667 - 2006
- [c5]Jörg Lücke, Christoph von der Malsburg:
Rapid Correspondence Finding in Networks of Cortical Columns. ICANN (1) 2006: 668-677 - 2005
- [c4]Jörg Lücke:
Dynamics of Cortical Columns - Sensitive Decision Making. ICANN (1) 2005: 25-30 - [c3]Jörg Lücke, Jan D. Bouecke:
Dynamics of Cortical Columns - Self-organization of Receptive Fields. ICANN (1) 2005: 31-37 - 2002
- [c2]Jörg Lücke, Christoph von der Malsburg, Rolf P. Würtz:
Macrocolumns as Decision Units. ICANN 2002: 57-62 - 2001
- [c1]Jörg Lücke:
Hilberticus - A Tool Deciding an Elementary Sublanguage of Set Theory. IJCAR 2001: 690-695
Informal and Other Publications
- 2023
- [i12]Dmytro Velychko, Simon Damm, Asja Fischer, Jörg Lücke:
Learning Sparse Codes with Entropy-Based ELBOs. CoRR abs/2311.01888 (2023) - 2022
- [i11]Jörg Lücke:
On the Convergence of the ELBO to Entropy Sums. CoRR abs/2209.03077 (2022) - 2020
- [i10]S. Hamid Mousavi, Jakob Drefs, Florian Hirschberger, Jörg Lücke:
Maximal Causes for Exponential Family Observables. CoRR abs/2003.02214 (2020) - [i9]Jörg Lücke, Dennis Forster, Zhenwen Dai:
The Evidence Lower Bound of Variational Autoencoders Converges to a Sum of Three Entropies. CoRR abs/2010.14860 (2020) - [i8]Enrico Guiraud, Jakob Drefs, Jörg Lücke:
Direct Evolutionary Optimization of Variational Autoencoders With Binary Latents. CoRR abs/2011.13704 (2020) - [i7]Jakob Drefs, Enrico Guiraud, Jörg Lücke:
Evolutionary Variational Optimization of Generative Models. CoRR abs/2012.12294 (2020) - 2019
- [i6]Georgios Exarchakis, Jörg Bornschein, Abdul-Saboor Sheikh, Zhenwen Dai, Marc Henniges, Jakob Drefs, Jörg Lücke:
ProSper - A Python Library for Probabilistic Sparse Coding with Non-Standard Priors and Superpositions. CoRR abs/1908.06843 (2019) - 2018
- [i5]Florian Hirschberger, Dennis Forster, Jörg Lücke:
Accelerated Training of Large-Scale Gaussian Mixtures by a Merger of Sublinear Approaches. CoRR abs/1810.00803 (2018) - 2017
- [i4]Dennis Forster, Jörg Lücke:
Truncated Variational EM for Semi-Supervised Neural Simpletrons. CoRR abs/1702.01997 (2017) - 2015
- [i3]Dennis Forster, Abdul-Saboor Sheikh, Jörg Lücke:
Neural Simpletrons - Minimalistic Probabilistic Networks for Learning With Few Labels. CoRR abs/1506.08448 (2015) - 2014
- [i2]Jacquelyn A. Shelton, Jan Gasthaus, Zhenwen Dai, Jörg Lücke, Arthur Gretton:
GP-select: Accelerating EM using adaptive subspace preselection. CoRR abs/1412.3411 (2014) - 2012
- [i1]Zhenwen Dai, Jörg Lücke:
Autonomous Cleaning of Corrupted Scanned Documents - A Generative Modeling Approach. CoRR abs/1201.2605 (2012)
Coauthor Index
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