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We propose a framework for analyzing and comparing distributions, allowing us to design statistical tests to determine if two samples are drawn from different distributions. Our test statistic is the largest difference in expectations over functions in the unit ball of a reproducing kernel Hilbert space (RKHS). We present two tests based on large deviation… (More)

- Arthur Gretton, Karsten M. Borgwardt, Malte J. Rasch, Bernhard Schölkopf, Alexander J. Smola
- Journal of Machine Learning Research
- 2012

We propose a framework for analyzing and comparing distributions, which we use to construct statistical tests to determine if two samples are drawn from different distributions. Our test statistic is the largest difference in expectations over functions in the unit ball of a reproducing kernel Hilbert space (RKHS), and is called the maximum mean discrepancy… (More)

MOTIVATION
Many problems in data integration in bioinformatics can be posed as one common question: Are two sets of observations generated by the same distribution? We propose a kernel-based statistical test for this problem, based on the fact that two distributions are different if and only if there exists at least one function having different expectation… (More)

- Marcelo A. Montemurro, Malte J. Rasch, Yusuke Murayama, Nikos K. Logothetis, Stefano Panzeri
- Current Biology
- 2008

We investigated the hypothesis that neurons encode rich naturalistic stimuli in terms of their spike times relative to the phase of ongoing network fluctuations rather than only in terms of their spike count. We recorded local field potentials (LFPs) and multiunit spikes from the primary visual cortex of anaesthetized macaques while binocularly presenting a… (More)

- Laurenz Wiskott, Malte J. Rasch, Gerd Kempermann
- Hippocampus
- 2006

The dentate gyrus is part of the hippocampal memory system and special in that it generates new neurons throughout life. Here we discuss the question of what the functional role of these new neurons might be. Our hypothesis is that they help the dentate gyrus to avoid the problem of catastrophic interference when adapting to new environments. We assume that… (More)

- Malte J. Rasch, Arthur Gretton, Yusuke Murayama, Wolfgang Maass, Nikos K. Logothetis
- Journal of neurophysiology
- 2008

We investigated whether it is possible to infer spike trains solely on the basis of the underlying local field potentials (LFPs). Using support vector machines and linear regression models, we found that in the primary visual cortex (V1) of monkeys, spikes can indeed be inferred from LFPs, at least with moderate success. Although there is a considerable… (More)

- Malte J. Rasch, Nikos K. Logothetis, Gabriel Kreiman
- The Journal of neuroscience : the official…
- 2009

Extracellular physiological recordings are typically separated into two frequency bands: local field potentials (LFPs) (a circuit property) and spiking multiunit activity (MUA). Recently, there has been increased interest in LFPs because of their correlation with functional magnetic resonance imaging blood oxygenation level-dependent measurements and the… (More)

- Malte J. Rasch, Klaus Schuch, Nikos K. Logothetis, Wolfgang Maass
- Journal of neurophysiology
- 2011

A major goal of computational neuroscience is the creation of computer models for cortical areas whose response to sensory stimuli resembles that of cortical areas in vivo in important aspects. It is seldom considered whether the simulated spiking activity is realistic (in a statistical sense) in response to natural stimuli. Because certain statistical… (More)

- Thomas Höfer, Malte J. Rasch
- Genome informatics. International Conference on…
- 2005

We analyse a stochastic model of transcription that describes transcription initiation by promoter activation and subsequent polymerase recruitment. Explicit expressions are derived for the control of an activator on the mean mRNA number and for the mRNA noise. Both properties are strongly influenced by the kinetics of promoter activation, mRNA synthesis… (More)

We describe a technique for comparing distributions without the need for density estimation as an intermediate step. Our approach relies on mapping the distributions into a Reproducing Kernel Hilbert Space. We apply this technique to construct a two-sample test, which is used for determining whether two sets of observations arise from the same distribution.… (More)