29 results
(View BibTeX file of all listed publications)

**Deep learning for the parameter estimation of tight-binding Hamiltonians**
University of Roma, La Sapienza, Italy, May 2020 (mastersthesis)

**Learning Algorithms, Invariances, and the Real World**
Technical University of Darmstadt, Germany, April 2020 (mastersthesis)

**Relative gradient optimization of the jacobian term in unsupervised deep learning**
2020 (misc)

**Learning explanations that are hard to vary**
2020 (misc)

**Advances in Latent Variable and Causal Models**
University of Cambridge, UK, 2020, (Cambridge-Tuebingen-Fellowship) (phdthesis)

**On the Fairness of Causal Algorithmic Recourse**
2020 (misc) Submitted

**A survey of algorithmic recourse: definitions, formulations, solutions, and prospects**
2020 (misc) Submitted

**A machine learning route between band mapping and band structure**
2020, *equal contribution (misc)

**Scaling Guarantees for Nearest Counterfactual Explanations**
2020 (misc) Submitted

**Nonparametric Disturbance Correction and Nonlinear Dual Control**
(24098), ETH Zurich, 2017 (phdthesis)

**Development and Evaluation of a Portable BCI System for Remote Data Acquisition**
Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2017 (mastersthesis)

**Brain-Computer Interfaces for patients with Amyotrophic Lateral Sclerosis**
Eberhard Karls Universität Tübingen, Germany, 2017 (phdthesis)

**Causal models for decision making via integrative inference**
University of Stuttgart, Germany, 2017 (phdthesis)

**Learning Optimal Configurations for Modeling Frowning by Transcranial Electrical Stimulation**
Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2017 (mastersthesis)

**Some thoughts about Gaussian Processes**
NIPS Workshop on Open Problems in Gaussian Processes for Machine Learning, December 2005 (talk)

ei
Chapelle, O.
**A taxonomy of semi-supervised learning algorithms**
Yahoo!, December 2005 (talk)

**Extension to Kernel Dependency Estimation with Applications to Robotics**
Biologische Kybernetik, Technische Universität Berlin, Berlin, November 2005 (phdthesis)

**Geometrical aspects of statistical learning theory**
Biologische Kybernetik, Darmstadt, Darmstadt, November 2005 (phdthesis)

**Implicit Surfaces For Modelling
Human Heads**
Biologische Kybernetik, Eberhard-Karls-Universität, Tübingen, September 2005 (diplomathesis)

**Machine Learning Methods for Brain-Computer Interdaces**
Biologische Kybernetik, University of Darmstadt, September 2005 (phdthesis)

**Building Sparse Large Margin Classifiers**
The 22nd International Conference on Machine Learning (ICML), August 2005 (talk)

**Learning from Labeled and Unlabeled Data on a Directed Graph**
The 22nd International Conference on Machine Learning, August 2005 (talk)

**Machine-Learning Approaches to BCI in Tübingen**
Brain-Computer Interface Technology, June 2005, Talk given by NJH. (talk)

**Efficient Adaptive Sampling of the Psychometric Function by Maximizing Information Gain**
Biologische Kybernetik, Eberhard-Karls University Tübingen, Tübingen, Germany, May 2005 (diplomathesis)

**Kernel Constrained Covariance for Dependence Measurement**
AISTATS, January 2005 (talk)