Linear controller for an inverted pendulum having restricted travel: A high-and-low gain approach. - Zongli Lin; Ali Saberi; Michael Gutmann; Yacov A. Shamash (Autom., 1996)

Learning encoding and decoding filters for data representation with a spiking neuron. - Michael Gutmann; Aapo Hyvärinen; Kazuyuki Aihara (IJCNN, 2008)

Toward data representation with spiking neurons. - Michael Gutmann; Kazuyuki Aihara (Artif. Life Robotics, 2008)

Learning reconstruction and prediction of natural stimuli by a population of spiking neurons. - Michael Gutmann; Aapo Hyvärinen (ESANN, 2009)

Learning Features by Contrasting Natural Images with Noise. - Michael Gutmann; Aapo Hyvärinen (ICANN (2), 2009)

Learning Natural Image Structure with a Horizontal Product Model. - Urs Köster; Jussi T. Lindgren; Michael Gutmann; Aapo Hyvärinen (ICA, 2009)

A Family of Computationally E cient and Simple Estimators for Unnormalized Statistical Models. - Miika Pihlaja; Michael Gutmann; Aapo Hyvärinen (UAI, 2010)

Noise-contrastive estimation: A new estimation principle for unnormalized statistical models. - Michael Gutmann; Aapo Hyvärinen (AISTATS, 2010)

Extracting Coactivated Features from Multiple Data Sets. - Michael Gutmann; Aapo Hyvärinen (ICANN (1), 2011)

Complex-Valued Independent Component Analysis of Natural Images. - Valero Laparra; Michael Gutmann; Jesús Malo; Aapo Hyvärinen (ICANN (2), 2011)

Bregman divergence as general framework to estimate unnormalized statistical models. - Michael Gutmann; Junichiro Hirayama (UAI, 2011)

Learning a selectivity-invariance-selectivity feature extraction architecture for images. - Michael Gutmann; Aapo Hyvärinen (ICPR, 2012)

A Family of Computationally Efficient and Simple Estimators for Unnormalized Statistical Models - Miika Pihlaja; Michael Gutmann; Aapo Hyvärinen (CoRR, 2012)

Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics. - Michael Gutmann; Aapo Hyvärinen (J. Mach. Learn. Res., 2012)

Topographic Analysis of Correlated Components. - Hiroaki Sasaki; Michael Gutmann; Hayaru Shouno; Aapo Hyvärinen (ACML, 2012)

Correlated topographic analysis: estimating an ordering of correlated components. - Hiroaki Sasaki; Michael Gutmann; Hayaru Shouno; Aapo Hyvärinen (Mach. Learn., 2013)

Estimating Dependency Structures for non-Gaussian Components with Linear and Energy Correlations. - Hiroaki Sasaki; Michael Gutmann; Hayaru Shouno; Aapo Hyvärinen (AISTATS, 2014)

Simultaneous Estimation of Nongaussian Components and Their Correlation Structure. - Hiroaki Sasaki; Michael Gutmann; Hayaru Shouno; Aapo Hyvärinen (Neural Comput., 2017)

Extending the statistical software package Engine for Likelihood-Free Inference. - Vasileios Gkolemis; Michael Gutmann (CoRR, 2020)

An Extendable Python Implementation of Robust Optimisation Monte Carlo. - Vasilis Gkolemis; Michael Gutmann; Henri Pesonen (CoRR, 2023)

An Extendable Python Implementation of Robust Optimization Monte Carlo. - Vasilis Gkolemis; Michael Gutmann; Henri Pesonen (J. Stat. Softw., 2024)