Michael Gutmann

23 papers A 4B 3C 1Journal 11Unranked 4

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Fast and Robust Simulation-Based Inference With Optimization Monte Carlo. CoRR Vasilis Gkolemis, Christos Diou, Michael Gutmann
2024	J	`jnl`	An Extendable J. Stat. Softw. Vasilis Gkolemis, Michael Gutmann, Henri Pesonen
2023	J	`jnl`	An Extendable Python Implementation of Robust Optimisation Monte Carlo. CoRR Vasilis Gkolemis, Michael Gutmann, Henri Pesonen
2020	J	`jnl`	Extending the statistical software package Engine for Likelihood-Free Inference. CoRR Vasileios Gkolemis, Michael Gutmann
2017	J	`jnl`	Simultaneous Estimation of Nongaussian Components and Their Correlation Structure. Neural Comput. Hiroaki Sasaki, Michael Gutmann, Hayaru Shouno, Aapo Hyvärinen
2014	A	`conf`	Estimating Dependency Structures for non-Gaussian Components with Linear and Energy Correlations. AISTATS Hiroaki Sasaki, Michael Gutmann, Hayaru Shouno, Aapo Hyvärinen
2013	J	`jnl`	Correlated topographic analysis: estimating an ordering of correlated components. Mach. Learn. Hiroaki Sasaki, Michael Gutmann, Hayaru Shouno, Aapo Hyvärinen
2012	J	`jnl`	A Family of Computationally Efficient and Simple Estimators for Unnormalized Statistical Models CoRR Miika Pihlaja, Michael Gutmann, Aapo Hyvärinen
2012	J	`jnl`	Bregman divergence as general framework to estimate unnormalized statistical models CoRR Michael Gutmann, Junichiro Hirayama
2012	B	`conf`	Learning a selectivity-invariance-selectivity feature extraction architecture for images. ICPR Michael Gutmann, Aapo Hyvärinen
2012	J	`jnl`	Noise-Contrastive Estimation of Unnormalized Statistical Models, with Applications to Natural Image Statistics. J. Mach. Learn. Res. Michael Gutmann, Aapo Hyvärinen
2012	C	`conf`	Topographic Analysis of Correlated Components. ACML Hiroaki Sasaki, Michael Gutmann, Hayaru Shouno, Aapo Hyvärinen
2011	A	`conf`	Bregman divergence as general framework to estimate unnormalized statistical models. UAI Michael Gutmann, Junichiro Hirayama
2011	—	`conf`	Complex-Valued Independent Component Analysis of Natural Images. ICANN (2) Valero Laparra, Michael Gutmann, Jesús Malo, Aapo Hyvärinen
2011	—	`conf`	Extracting Coactivated Features from Multiple Data Sets. ICANN (1) Michael Gutmann, Aapo Hyvärinen
2010	A	`conf`	A Family of Computationally E cient and Simple Estimators for Unnormalized Statistical Models. UAI Miika Pihlaja, Michael Gutmann, Aapo Hyvärinen
2010	A	`conf`	Noise-contrastive estimation: A new estimation principle for unnormalized statistical models. AISTATS Michael Gutmann, Aapo Hyvärinen
2009	—	`conf`	Learning Features by Contrasting Natural Images with Noise. ICANN (2) Michael Gutmann, Aapo Hyvärinen
2009	—	`conf`	Learning Natural Image Structure with a Horizontal Product Model. ICA Urs Köster, Jussi T. Lindgren, Michael Gutmann, Aapo Hyvärinen
2009	B	`conf`	Learning reconstruction and prediction of natural stimuli by a population of spiking neurons. ESANN Michael Gutmann, Aapo Hyvärinen
2008	B	`conf`	Learning encoding and decoding filters for data representation with a spiking neuron. IJCNN Michael Gutmann, Aapo Hyvärinen, Kazuyuki Aihara
2008	J	`jnl`	Toward data representation with spiking neurons. Artif. Life Robotics Michael Gutmann, Kazuyuki Aihara
1996	J	`jnl`	Linear controller for an inverted pendulum having restricted travel: A high-and-low gain approach. Autom. Zongli Lin, Ali Saberi, Michael Gutmann, Yacov A. Shamash