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- Michael Gutmann, Aapo Hyvärinen
- AISTATS
- 2010

We present a new estimation principle for parameterized statistical models. The idea is to perform nonlinear logistic regression to discriminate between the observed data and some artificially generated noise, using the model log-density function in the regression nonlinearity. We show that this leads to a consistent (convergent) estimator of the parameters… (More)

- Michael Gutmann, Aapo Hyvärinen
- Journal of Machine Learning Research
- 2012

We consider the task of estimating, from observed data, a probabilistic model that is parameterized by a finite number of parameters. In particular, we are considering the situation where the model probability density function is unnormalized. That is, the model is only specified up to the partition function. The partition function normalizes a model so… (More)

- Zongli Lin, Ali Saberi, Michael Gutmann, Yacov A. Shamash
- Automatica
- 1996

We present a novel extension to Independent Component Analysis (ICA), where the data is generated as the product of two sub-models, each of which follow an ICA model, and which combine in a horizontal fashion. This is in contrast to previous nonlinear extensions to ICA which were based on a hierarchy of layers. We apply the product model to natural image… (More)

- Aapo Hyvärinen, Michael Gutmann, Patrik O Hoyer
- BMC Neuroscience
- 2004

It has been shown that the classical receptive fields of simple and complex cells in the primary visual cortex emerge from the statistical properties of natural images by forcing the cell responses to be maximally sparse or independent. We investigate how to learn features beyond the primary visual cortex from the statistical properties of modelled… (More)

A fundamental question in visual neuroscience is: Why are the receptive fields and response properties of visual neurons as they are? A modern approach to this problem emphasizes the importance of adaptation to ecologically valid input. In this paper, we will review work on modelling statistical regularities in ecologically valid visual input (" natural… (More)

- Michael Gutmann, Junichiro Hirayama
- UAI
- 2011

We show that the Bregman divergence provides a rich framework to estimate unnor-malized statistical models for continuous or discrete random variables, that is, models which do not integrate or sum to one, respectively. We prove that recent estimation methods such as noise-contrastive estimation, ratio matching, and score matching belong to the proposed… (More)

- Mario Gerecke, Genaro Bierhance, Michael Gutmann, Nikolaus P Ernsting, Arnulf Rosspeintner
- The Review of scientific instruments
- 2016

Sum frequency mixing of fluorescence and ∼1300 nm gate pulses, in a thin β-barium borate crystal and non-collinear type II geometry, is quantified as part of a femtosecond fluorimeter [X.-X. Zhang et al., Rev. Sci. Instrum. 82, 063108 (2011)]. For a series of fixed phasematching angles, the upconversion efficiency is measured depending on fluorescence… (More)

- Michael U Gutmann, Aapo Hyvärinen
- Journal of physiology, Paris
- 2013

An important property of visual systems is to be simultaneously both selective to specific patterns found in the sensory input and invariant to possible variations. Selectivity and invariance (tolerance) are opposing requirements. It has been suggested that they could be joined by iterating a sequence of elementary selectivity and tolerance computations. It… (More)

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