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Journal Articles
- 2024
[j6]Vasilis Gkolemis, Michael Gutmann, Henri Pesonen:
An Extendable Python Implementation of Robust Optimization Monte Carlo. J. Stat. Softw. 110(2) (2024)- 2017
- [j5]Hiroaki Sasaki, Michael Gutmann, Hayaru Shouno, Aapo Hyvärinen
:
Simultaneous Estimation of Nongaussian Components and Their Correlation Structure. Neural Comput. 29(11) (2017) - 2013
- [j4]Hiroaki Sasaki, Michael Gutmann, Hayaru Shouno, Aapo Hyvärinen:
Correlated topographic analysis: estimating an ordering of correlated components. Mach. Learn. 92(2-3): 285-317 (2013) - 2012
- [j3]Michael Gutmann, Aapo Hyvärinen:
Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics. J. Mach. Learn. Res. 13: 307-361 (2012) - 2008
- [j2]Michael Gutmann, Kazuyuki Aihara:
Toward data representation with spiking neurons. Artif. Life Robotics 12(1-2): 223-226 (2008) - 1996
- [j1]Zongli Lin, Ali Saberi, Michael Gutmann, Yacov A. Shamash:
Linear controller for an inverted pendulum having restricted travel: A high-and-low gain approach. Autom. 32(6): 933-937 (1996)
Conference and Workshop Papers
- 2014
- [c12]Hiroaki Sasaki, Michael Gutmann, Hayaru Shouno, Aapo Hyvärinen:
Estimating Dependency Structures for non-Gaussian Components with Linear and Energy Correlations. AISTATS 2014: 868-876 - 2012
- [c11]Michael Gutmann, Aapo Hyvärinen:
Learning a selectivity-invariance-selectivity feature extraction architecture for images. ICPR 2012: 918-921 - [c10]Hiroaki Sasaki, Michael Gutmann, Hayaru Shouno, Aapo Hyvärinen:
Topographic Analysis of Correlated Components. ACML 2012: 365-378 - 2011
- [c9]Valero Laparra, Michael Gutmann, Jesús Malo, Aapo Hyvärinen:
Complex-Valued Independent Component Analysis of Natural Images. ICANN (2) 2011: 213-220 - [c8]Michael Gutmann, Aapo Hyvärinen:
Extracting Coactivated Features from Multiple Data Sets. ICANN (1) 2011: 323-330 - [c7]Michael Gutmann, Junichiro Hirayama:
Bregman divergence as general framework to estimate unnormalized statistical models. UAI 2011: 283-290 - 2010
- [c6]Miika Pihlaja, Michael Gutmann, Aapo Hyvärinen:
A Family of Computationally E cient and Simple Estimators for Unnormalized Statistical Models. UAI 2010: 442-449 - [c5]Michael Gutmann, Aapo Hyvärinen:
Noise-contrastive estimation: A new estimation principle for unnormalized statistical models. AISTATS 2010: 297-304 - 2009
- [c4]Michael Gutmann, Aapo Hyvärinen:
Learning reconstruction and prediction of natural stimuli by a population of spiking neurons. ESANN 2009 - [c3]Michael Gutmann, Aapo Hyvärinen:
Learning Features by Contrasting Natural Images with Noise. ICANN (2) 2009: 623-632 - [c2]Urs Köster, Jussi T. Lindgren, Michael Gutmann, Aapo Hyvärinen:
Learning Natural Image Structure with a Horizontal Product Model. ICA 2009: 507-514 - 2008
- [c1]Michael Gutmann, Aapo Hyvärinen, Kazuyuki Aihara:
Learning encoding and decoding filters for data representation with a spiking neuron. IJCNN 2008: 243-248
Informal and Other Publications
- 2023
- [i4]Vasilis Gkolemis, Michael Gutmann, Henri Pesonen:
An Extendable Python Implementation of Robust Optimisation Monte Carlo. CoRR abs/2309.10612 (2023) - 2020
- [i3]Vasileios Gkolemis, Michael Gutmann:
Extending the statistical software package Engine for Likelihood-Free Inference. CoRR abs/2011.03977 (2020) - 2012
- [i2]Michael Gutmann, Junichiro Hirayama:
Bregman divergence as general framework to estimate unnormalized statistical models. CoRR abs/1202.3727 (2012) - [i1]Miika Pihlaja, Michael Gutmann, Aapo Hyvärinen:
A Family of Computationally Efficient and Simple Estimators for Unnormalized Statistical Models. CoRR abs/1203.3506 (2012)
Coauthor Index
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