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2016


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Autofocusing-based correction of B0 fluctuation-induced ghosting

Loktyushin, A., Ehses, P., Schölkopf, B., Scheffler, K.

24th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM), May 2016 (poster)

ei

link (url) [BibTex]

2016


link (url) [BibTex]


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Special Issue on Causal Discovery and Inference

Zhang, K., Li, J., Bareinboim, E., Schölkopf, B., Pearl, J.

ACM Transactions on Intelligent Systems and Technology (TIST), 7(2), January 2016, (Guest Editors) (misc)

ei

[BibTex]

[BibTex]


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Empirical Inference (2010-2015)
Scientific Advisory Board Report, 2016 (misc)

ei

pdf [BibTex]

pdf [BibTex]


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Novel Random Forest based framework enables the segmentation of cerebral ischemic regions using multiparametric MRI

Katiyar, P., Castaneda, S., Patzwaldt, K., Russo, F., Poli, S., Ziemann, U., Disselhorst, J. A., Pichler, B. J.

European Molecular Imaging Meeting, 2016 (poster)

ei

link (url) [BibTex]

link (url) [BibTex]


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PGO wave-triggered functional MRI: mapping the networks underlying synaptic consolidation

Logothetis, N. K., Murayama, Y., Ramirez-Villegas, J. F., Besserve, M., Evrard, H.

47th Annual Meeting of the Society for Neuroscience (Neuroscience), 2016 (poster)

ei

[BibTex]

[BibTex]


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Unsupervised Domain Adaptation in the Wild : Dealing with Asymmetric Label Set

Mittal, A., Raj, A., Namboodiri, V. P., Tuytelaars, T.

2016 (misc)

ei

Arxiv [BibTex]

Arxiv [BibTex]


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Multiparametric Imaging of Ischemic Stroke using [89Zr]-Desferal-EPO-PET/MRI in combination with Gaussian Mixture Modeling enables unsupervised lesions identification

Castaneda, S., Katiyar, P., Russo, F., Maurer, A., Patzwaldt, K., Poli, S., Calaminus, C., Disselhorst, J. A., Ziemann, U., Pichler, B. J.

European Molecular Imaging Meeting, 2016 (poster)

ei

link (url) [BibTex]

link (url) [BibTex]


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Statistical source separation of rhythmic LFP patterns during sharp wave ripples in the macaque hippocampus

Ramirez-Villegas, J. F., Logothetis, N. K., Besserve, M.

47th Annual Meeting of the Society for Neuroscience (Neuroscience), 2016 (poster)

ei

[BibTex]

[BibTex]


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Hippocampal neural events predict ongoing brain-wide BOLD activity

Besserve, M., Logothetis, N. K.

47th Annual Meeting of the Society for Neuroscience (Neuroscience), 2016 (poster)

ei

[BibTex]

[BibTex]

2015


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easyGWAS: An Integrated Computational Framework for Advanced Genome-Wide Association Studies

Grimm, Dominik

Eberhard Karls Universität Tübingen, November 2015 (phdthesis)

ei

[BibTex]

2015


[BibTex]


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Causal Discovery Beyond Conditional Independences

Sgouritsa, E.

Eberhard Karls Universität Tübingen, Germany, October 2015 (phdthesis)

ei

link (url) [BibTex]

link (url) [BibTex]


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Diversity of sharp wave-ripples in the CA1 of the macaque hippocampus and their brain wide signatures

Ramirez-Villegas, J. F., Logothetis, N. K., Besserve, M.

45th Annual Meeting of the Society for Neuroscience (Neuroscience 2015), October 2015 (poster)

ei

link (url) [BibTex]

link (url) [BibTex]


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From Points to Probability Measures: A Statistical Learning on Distributions with Kernel Mean Embedding

Muandet, K.

University of Tübingen, Germany, University of Tübingen, Germany, September 2015 (phdthesis)

ei

[BibTex]

[BibTex]


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Machine Learning Approaches to Image Deconvolution

Schuler, C.

University of Tübingen, Germany, University of Tübingen, Germany, September 2015 (phdthesis)

ei

[BibTex]

[BibTex]


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Retrospective rigid motion correction of undersampled MRI data

Loktyushin, A., Babayeva, M., Gallichan, D., Krueger, G., Scheffler, K., Kober, T.

23rd Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine, ISMRM, June 2015 (poster)

ei

[BibTex]

[BibTex]


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Improving Quantitative Susceptibility and R2* Mapping by Applying Retrospective Motion Correction

Feng, X., Loktyushin, A., Deistung, A., Reichenbach, J. R.

23rd Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine, ISMRM, June 2015 (poster)

ei

[BibTex]

[BibTex]


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Blind Retrospective Motion Correction of MR Images

Loktyushin, A.

University of Tübingen, Germany, May 2015 (phdthesis)

ei

[BibTex]

[BibTex]


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Increasing the sensitivity of Kepler to Earth-like exoplanets

Foreman-Mackey, D., Hogg, D., Schölkopf, B., Wang, D.

Workshop: 225th American Astronomical Society Meeting 2015 , pages: 105.01D, 2015 (poster)

ei

Web link (url) [BibTex]

Web link (url) [BibTex]


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Calibrating the pixel-level Kepler imaging data with a causal data-driven model

Wang, D., Foreman-Mackey, D., Hogg, D., Schölkopf, B.

Workshop: 225th American Astronomical Society Meeting 2015 , pages: 258.08, 2015 (poster)

ei

Web link (url) [BibTex]

Web link (url) [BibTex]


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A Cognitive Brain-Computer Interface for Patients with Amyotrophic Lateral Sclerosis

Hohmann, M.

Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

ei

[BibTex]

[BibTex]


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Assessment of tumor heterogeneity using unsupervised graph based clustering of multi-modality imaging data

Katiyar, P., Divine, M. R., Pichler, B. J., Disselhorst, J. A.

European Molecular Imaging Meeting, 2015 (poster)

ei

[BibTex]

[BibTex]


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Sequential Image Deconvolution Using Probabilistic Linear Algebra

Gao, M.

Technical University of Munich, Germany, 2015 (mastersthesis)

ei

[BibTex]

[BibTex]


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Disparity estimation from a generative light field model

Köhler, R., Schölkopf, B., Hirsch, M.

IEEE International Conference on Computer Vision (ICCV 2015), Workshop on Inverse Rendering, 2015, Note: This work has been presented as a poster and is not included in the workshop proceedings. (poster)

ei

[BibTex]

[BibTex]


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Causal Inference in Neuroimaging

Casarsa de Azevedo, L.

Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

ei

[BibTex]

[BibTex]


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The effect of frowning on attention

Ibarra Chaoul, A.

Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

ei

[BibTex]

[BibTex]

2014


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Modeling the polygenic architecture of complex traits

Rakitsch, Barbara

Eberhard Karls Universität Tübingen, November 2014 (phdthesis)

ei

[BibTex]

2014


[BibTex]


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Dynamical source analysis of hippocampal sharp-wave ripple episodes

Ramirez-Villegas, J. F., Logothetis, N. K., Besserve, M.

Bernstein Conference, 2014 (poster)

ei

DOI [BibTex]

DOI [BibTex]


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A Novel Causal Inference Method for Time Series

Shajarisales, N.

Eberhard Karls Universität Tübingen, Germany, Eberhard Karls Universität Tübingen, Germany, 2014 (mastersthesis)

ei

PDF [BibTex]

PDF [BibTex]


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FID-guided retrospective motion correction based on autofocusing

Babayeva, M., Loktyushin, A., Kober, T., Granziera, C., Nickisch, H., Gruetter, R., Krueger, G.

Joint Annual Meeting ISMRM-ESMRMB, Milano, Italy, 2014 (poster)

ei

[BibTex]

[BibTex]


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Cluster analysis of sharp-wave ripple field potential signatures in the macaque hippocampus

Ramirez-Villegas, J. F., Logothetis, N. K., Besserve, M.

Computational and Systems Neuroscience Meeting (COSYNE), 2014 (poster)

ei

[BibTex]

[BibTex]


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A global analysis of extreme events and consequences for the terrestrial carbon cycle

Zscheischler, J.

Diss. No. 22043, ETH Zurich, Switzerland, ETH Zurich, Switzerland, 2014 (phdthesis)

ei

[BibTex]

[BibTex]


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Development of advanced methods for improving astronomical images

Schmeißer, N.

Eberhard Karls Universität Tübingen, Germany, Eberhard Karls Universität Tübingen, Germany, 2014 (diplomathesis)

ei

[BibTex]

[BibTex]


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The Feasibility of Causal Discovery in Complex Systems: An Examination of Climate Change Attribution and Detection

Lacosse, E.

Graduate Training Centre of Neuroscience, University of Tübingen, Germany, Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2014 (mastersthesis)

ei

[BibTex]

[BibTex]


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Causal Discovery in the Presence of Time-Dependent Relations or Small Sample Size

Huang, B.

Graduate Training Centre of Neuroscience, University of Tübingen, Germany, Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2014 (mastersthesis)

ei

[BibTex]

[BibTex]


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oxel level [18]F-FDG PET/MRI unsupervised segmentation of the tumor microenvironment

Katiyar, P., Divine, M. R., Pichler, B. J., Disselhorst, J. A.

World Molecular Imaging Conference, 2014 (poster)

ei

[BibTex]

[BibTex]


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Analysis of Distance Functions in Graphs

Alamgir, M.

University of Hamburg, Germany, University of Hamburg, Germany, 2014 (phdthesis)

ei

[BibTex]

[BibTex]

2009


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Learning Probabilistic Models via Bayesian Inverse Planning

Boularias, A., Chaib-Draa, B.

NIPS Workshop on Probabilistic Approaches for Robotics and Control, December 2009 (poster)

ei

PDF Web [BibTex]

2009


PDF Web [BibTex]


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Bayesian Quadratic Reinforcement Learning

Hennig, P., Stern, D., Graepel, T.

NIPS Workshop on Probabilistic Approaches for Robotics and Control, December 2009 (poster)

ei pn

PDF Web [BibTex]

PDF Web [BibTex]


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Policy Transfer in Apprenticeship Learning

Boularias, A., Chaib-Draa, B.

NIPS Workshop on Transfer Learning for Structured Data (TLSD-09), December 2009 (poster)

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Clinical PET/MRI-System and Its Applications with MRI Based Attenuation Correction

Kolb, A., Hofmann, M., Sossi, V., Wehrl, H., Sauter, A., Schmid, A., Schlemmer, H., Claussen, C., Pichler, B.

IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC 2009), 2009, pages: 1, October 2009 (poster)

Abstract
Clinical PET/MRI is an emerging new hybrid imaging modality. In addition to provide an unique possibility for multifunctional imaging with temporally and spatially matched data, it also provides anatomical information that can also be used for attenuation correction with no radiation exposure to the subjects. A plus of combined compared to sequential PET and MR imaging is the reduction of total scan time. Here we present our initial experience with a hybrid brain PET/MRI system. Due to the ethical approval patient scans could only be performed after a diagnostic PET/CT. We estimate that in approximately 50% of the cases PET/MRI was of superior diagnostic value compared to PET/CT and was able to provide additional information, such as DTI, spectroscopy and Time Of Flight (TOF) angiography. Here we present 3 patient cases in oncology, a retropharyngeal carcinoma in neurooncology, a relapsing meningioma and in neurology a pharyngeal carcinoma in addition to an infraction of the right hemisphere. For quantitative PET imaging attenuation correction is obligatory. In current PET/MRI setup we used our MRI based atlas method for calculating the mu-map for attenuation correction. MR-based attenuation correction accuracy was quantitatively compared to CT-based PET attenuation correction. Extensive studies to assess potential mutual interferences between PET and MR imaging modalities as well as NEMA measurements have been performed. The first patient studies as well as the phantom tests clearly demonstrated the overall good imaging performance of this first human PET/MRI system. Ongoing work concentrates on advanced normalization and reconstruction methods incorporating count-rate based algorithms.

ei

Web [BibTex]

Web [BibTex]


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Kernel Learning Approaches for Image Classification

Gehler, PV.

Biologische Kybernetik, Universität des Saarlandes, Saarbrücken, Germany, October 2009 (phdthesis)

Abstract
This thesis extends the use of kernel learning techniques to specific problems of image classification. Kernel learning is a paradigm in the field of machine learning that generalizes the use of inner products to compute similarities between arbitrary objects. In image classification one aims to separate images based on their visual content. We address two important problems that arise in this context: learning with weak label information and combination of heterogeneous data sources. The contributions we report on are not unique to image classification, and apply to a more general class of problems. We study the problem of learning with label ambiguity in the multiple instance learning framework. We discuss several different image classification scenarios that arise in this context and argue that the standard multiple instance learning requires a more detailed disambiguation. Finally we review kernel learning approaches proposed for this problem and derive a more efficient algorithm to solve them. The multiple kernel learning framework is an approach to automatically select kernel parameters. We extend it to its infinite limit and present an algorithm to solve the resulting problem. This result is then applied in two directions. We show how to learn kernels that adapt to the special structure of images. Finally we compare different ways of combining image features for object classification and present significant improvements compared to previous methods.

ei

PDF [BibTex]

PDF [BibTex]


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A PAC-Bayesian Approach to Structure Learning

Seldin, Y.

Biologische Kybernetik, The Hebrew University of Jerusalem, Israel, September 2009 (phdthesis)

ei

PDF [BibTex]

PDF [BibTex]


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A flowering-time gene network model for association analysis in Arabidopsis thaliana

Klotzbücher, K., Kobayashi, Y., Shervashidze, N., Borgwardt, K., Weigel, D.

2009(39):95-96, German Conference on Bioinformatics (GCB '09), September 2009 (poster)

Abstract
In our project we want to determine a set of single nucleotide polymorphisms (SNPs), which have a major effect on the flowering time of Arabidopsis thaliana. Instead of performing a genome-wide association study on all SNPs in the genome of Arabidopsis thaliana, we examine the subset of SNPs from the flowering-time gene network model. We are interested in how the results of the association study vary when using only the ascertained subset of SNPs from the flowering network model, and when additionally using the information encoded by the structure of the network model. The network model is compiled from the literature by manual analysis and contains genes which have been found to affect the flowering time of Arabidopsis thaliana [Far+08; KW07]. The genes in this model are annotated with the SNPs that are located in these genes, or in near proximity to them. In a baseline comparison between the subset of SNPs from the graph and the set of all SNPs, we omit the structural information and calculate the correlation between the individual SNPs and the flowering time phenotype by use of statistical methods. Through this we can determine the subset of SNPs with the highest correlation to the flowering time. In order to further refine this subset, we include the additional information provided by the network structure by conducting a graph-based feature pre-selection. In the further course of this project we want to validate and examine the resulting set of SNPs and their corresponding genes with experimental methods.

ei

PDF Web [BibTex]

PDF Web [BibTex]


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Initial Data from a first PET/MRI-System and its Applications in Clinical Studies Using MRI Based Attenuation Correction

Kolb, A., Hofmann, M., Sossi, V., Wehrl, H., Sauter, A., Schmid, A., Judenhofer, M., Schlemmer, H., Claussen, C., Pichler, B.

2009 World Molecular Imaging Congress, 2009, pages: 1200, September 2009 (poster)

ei

Web [BibTex]

Web [BibTex]


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A High-Speed Object Tracker from Off-the-Shelf Components

Lampert, C., Peters, J.

First IEEE Workshop on Computer Vision for Humanoid Robots in Real Environments at ICCV 2009, 1, pages: 1, September 2009 (poster)

Abstract
We introduce RTblob, an open-source real-time vision system for 3D object detection that achieves over 200 Hz tracking speed with only off-the-shelf hardware component. It allows fast and accurate tracking of colored objects in 3D without expensive and often custom-built hardware, instead making use of the PC graphics cards for the necessary image processing operations.

ei

PDF Web [BibTex]

PDF Web [BibTex]