| 2014 | AISTATS | Estimating Dependency Structures for non-Gaussian Components with Linear and Energy Correlations. | Hiroaki Sasaki, Michael Gutmann, Hayaru Shouno, Aapo Hyvrinen |
| 2012 | ICPR | Learning a selectivity-invariance-selectivity feature extraction architecture for images. | Michael Gutmann, Aapo Hyvrinen |
| 2011 | ICANN | Extracting Coactivated Features from Multiple Data Sets. | Michael Gutmann, Aapo Hyvrinen |
| 2011 | ICANN | Complex-Valued Independent Component Analysis of Natural Images. | Valero Laparra, Michael Gutmann, Jess Malo, Aapo Hyvrinen |
| 2011 | UAI | Bregman divergence as general framework to estimate unnormalized statistical models. | Michael Gutmann, Junichiro Hirayama |
| 2010 | UAI | A Family of Computationally E cient and Simple Estimators for Unnormalized Statistical Models. | Miika Pihlaja, Michael Gutmann, Aapo Hyvrinen |
| 2009 | ESANN | Learning reconstruction and prediction of natural stimuli by a population of spiking neurons. | Michael Gutmann, Aapo Hyvrinen |
| 2009 | ICANN | Learning Features by Contrasting Natural Images with Noise. | Michael Gutmann, Aapo Hyvrinen |
| 2009 | IDA | Learning Natural Image Structure with a Horizontal Product Model. | Urs Kster, Jussi T. Lindgren, Michael Gutmann, Aapo Hyvrinen |
| 2008 | IJCNN | Learning encoding and decoding filters for data representation with a spiking neuron. | Michael Gutmann, Aapo Hyvrinen, Kazuyuki Aihara |