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Empirical Inference Bachelor Thesis Navigating the Ocean of Biases: Political Bias Attribution in Language Models via Causal Structures Jenny, D. ETH Zurich, Switzerland, November 2023, external supervision (Published) BibTeX
Empirical Inference Bachelor Thesis Automatic Segmentation and Labelling for Robot Table Tennis Time Series Lutz, P. Technical University Darmstadt, Germany, August 2019 (Published) BibTeX
Empirical Inference Thesis Development of advanced methods for improving astronomical images Schmeißer, N. Eberhard Karls Universität Tübingen, Germany, Eberhard Karls Universität Tübingen, Germany, 2014 BibTeX
Empirical Inference Probabilistic Numerics Thesis Camera-specific Image Denoising Schober, M. Eberhard Karls Universität Tübingen, Germany, October 2013 (Published) PDF BibTeX
Empirical Inference Thesis Automatische Seitenkettenzuordnung zur NMR Proteinstrukturaufklärung mittels ganzzahliger linearer Programmierung Hooge, J. University of Tübingen, Germany, 2012 BibTeX
Empirical Inference Probabilistic Numerics Thesis Nonparametric System Identification and Control for Periodic Error Correction in Telescopes Klenske, E. D. University of Stuttgart, 2012 (Published) PDF BibTeX
Empirical Inference Thesis Inferring High-Dimensional Causal Relations using Free Probability Theory Zscheischler, J. Humboldt Universität Berlin, Germany, August 2010 PDF BibTeX
Empirical Inference Thesis Semi-supervised Subspace Learning and Application to Human Functional Magnetic Brain Resonance Imaging Data Shelton, J. Biologische Kybernetik, Eberhard Karls Universität, Tübingen, Germany, July 2010 PDF BibTeX
Empirical Inference Thesis Quantitative Evaluation of MR-based Attenuation Correction for Positron Emission Tomography (PET) Mantlik, F. Biologische Kybernetik, Universität Mannheim, Germany, March 2010 BibTeX
Empirical Inference Thesis Detecting the mincut in sparse random graphs Köhler, R. Eberhard Karls Universität Tübingen, Germany, 2010 BibTeX
Empirical Inference Thesis Finding Gene-Gene Interactions using Support Vector Machines Rakitsch, B. Eberhard Karls Universität Tübingen, Germany, 2010 BibTeX
Empirical Inference Thesis Hierarchical Clustering and Density Estimation Based on k-nearest-neighbor graphs Drewe, P. Eberhard Karls Universität Tübingen, Germany, 2009 BibTeX
Empirical Inference Thesis Motor Control and Learning in Table Tennis Mülling, K. Eberhard Karls Universität Tübingen, Gerrmany, 2009 BibTeX
Empirical Inference Thesis Reinforcement Learning for Motor Primitives Kober, J. Biologische Kybernetik, University of Stuttgart, Stuttgart, Germany, August 2008 PDF BibTeX
Empirical Inference Thesis Asymmetries of Time Series under Inverting their Direction Peters, J. Biologische Kybernetik, University of Heidelberg, August 2008 PDF BibTeX
Empirical Inference Thesis Pairwise Correlations and Multineuronal Firing Patterns in Primary Visual Cortex Berens, P. Biologische Kybernetik, Eberhard Karls Universität Tübingen, Tübingen, Germany, April 2008 BibTeX
Empirical Inference Thesis Development and Application of a Python Scripting Framework for BCI2000 Schreiner, T. Biologische Kybernetik, Eberhard-Karls-Universität Tübingen, Tübingen, Germany, January 2008 BibTeX
Empirical Inference Thesis Statistical Learning Theory Approaches to Clustering Jegelka, S. Biologische Kybernetik, Eberhard-Karls-Universität Tübingen, Tübingen, Germany, November 2007 PDF BibTeX
Empirical Inference Thesis Error Correcting Codes for the P300 Visual Speller Biessmann, F. Biologische Kybernetik, Eberhard-Karls-Universität Tübingen, Tübingen, Germany, July 2007
The aim of brain-computer interface (BCI) research is to establish a communication system based on intentional modulation of brain activity. This is accomplished by classifying patterns of brain ac- tivity, volitionally induced by the user. The BCI presented in this study is based on a classical paradigm as proposed by (Farwell and Donchin, 1988), the P300 visual speller. Recording electroencephalo- grams (EEG) from the scalp while presenting letters successively to the user, the speller can infer from the brain signal which letter the user was focussing on. Since EEG recordings are noisy, usually many repetitions are needed to detect the correct letter. The focus of this study was to improve the accuracy of the visual speller applying some basic principles from information theory: Stimulus sequences of the speller have been modified into error-correcting codes. Additionally a language model was incorporated into the probabilistic letter de- coder. Classification of single EEG epochs was less accurate using error correcting codes. However, the novel code could compensate for that such that overall, letter accuracies were as high as or even higher than for classical stimulus codes. In particular at high noise levels, error-correcting decoding achieved higher letter accuracies.
PDF BibTeX
Empirical Inference Thesis A priori Knowledge from Non-Examples Sinz, F. Biologische Kybernetik, Eberhard-Karls-Universität Tübingen, Tübingen, Germany, March 2007 PDF Web BibTeX
Empirical Inference Thesis Development of a Brain-Computer Interface Approach Based on Covert Attention to Tactile Stimuli Raths, C. University of Tübingen, Germany, University of Tübingen, Germany, January 2007 BibTeX
Empirical Inference Thesis A Machine Learning Approach for Estimating the Attenuation Map for a Combined PET/MR Scanner Hofmann, M. Biologische Kybernetik, Max-Planck Institute for Biological Cybernetics, Tübingen, Germany, 2007 BibTeX
Empirical Inference Thesis Kernel PCA for Image Compression Huhle, B. Biologische Kybernetik, Eberhard-Karls-Universität, Tübingen, Germany, April 2006 PDF BibTeX
Empirical Inference Thesis Implicit Surfaces For Modelling Human Heads Steinke, F. Biologische Kybernetik, Eberhard-Karls-Universität, Tübingen, September 2005 BibTeX
Empirical Inference Thesis Efficient Adaptive Sampling of the Psychometric Function by Maximizing Information Gain Tanner, T. Biologische Kybernetik, Eberhard-Karls University Tübingen, Tübingen, Germany, May 2005
A common task in psychophysics is to measure the psychometric function. A psychometric function can be described by its shape and four parameters: offset or threshold, slope or width, false alarm rate or chance level and miss or lapse rate. Depending on the parameters of interest some points on the psychometric function may be more informative than others. Adaptive methods attempt to place trials on the most informative points based on the data collected in previous trials. A new Bayesian adaptive psychometric method placing trials by minimising the expected entropy of the posterior probabilty dis- tribution over a set of possible stimuli is introduced. The method is more flexible, faster and at least as efficient as the established method (Kontsevich and Tyler, 1999). Comparably accurate (2dB) threshold and slope estimates can be obtained after about 30 and 500 trials, respectively. By using a dynamic termination criterion the efficiency can be further improved. The method can be applied to all experimental designs including yes/no designs and allows acquisition of any set of free parameters. By weighting the importance of parameters one can include nuisance parameters and adjust the relative expected errors. Use of nuisance parameters may lead to more accurate estimates than assuming a guessed fixed value. Block designs are supported and do not harm the performance if a sufficient number of trials are performed. The method was evaluated by computer simulations in which the role of parametric assumptions, its robustness, the quality of different point estimates, the effect of dynamic termination criteria and many other settings were investigated.
BibTeX
Empirical Inference Thesis Real-Time Face Detection Kienzle, W. Biologische Kybernetik, Eberhard-Karls-Universitaet Tuebingen, Tuebingen, Germany, October 2003 BibTeX
Empirical Inference Thesis m-Alternative Forced Choice—Improving the Efficiency of the Method of Constant Stimuli Jäkel, F. Biologische Kybernetik, Graduate School for Neural and Behavioural Sciences, Tübingen, 2003 BibTeX
Empirical Inference Thesis Variationsverfahren zur Untersuchung von Grundzustandseigenschaften des Ein-Band Hubbard-Modells Eichhorn, J. Biologische Kybernetik, Technische Universität Dresden, Dresden/Germany, May 2001
Using different modifications of a new variational approach, statical groundstate properties of the one-band Hubbard model such as energy and staggered magnetisation are calculated. By taking into account additional fluctuations, the method ist gradually improved so that a very good description of the energy in one and two dimensions can be achieved. After a detailed discussion of the application in one dimension, extensions for two dimensions are introduced. By use of a modified version of the variational ansatz in particular a description of the quantum phase transition for the magnetisation should be possible.
PostScript BibTeX