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2015


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Inference of Cause and Effect with Unsupervised Inverse Regression

Sgouritsa, E., Janzing, D., Hennig, P., Schölkopf, B.

In Proceedings of the 18th International Conference on Artificial Intelligence and Statistics, 38, pages: 847-855, JMLR Workshop and Conference Proceedings, (Editors: Lebanon, G. and Vishwanathan, S.V.N.), JMLR.org, AISTATS, 2015 (inproceedings)

Web PDF [BibTex]

Web PDF [BibTex]


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Distinguishing Cause from Effect Based on Exogeneity

Zhang, K., Zhang, J., Schölkopf, B.

In Fifteenth Conference on Theoretical Aspects of Rationality and Knowledge, pages: 261-271, (Editors: Ramanujam, R.), TARK, 2015 (inproceedings)

[BibTex]

[BibTex]


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Developing biorobotics for veterinary research into cat movements

Mariti, C., Muscolo, G., Peters, J., Puig, D., Recchiuto, C., Sighieri, C., Solanas, A., von Stryk, O.

Journal of Veterinary Behavior: Clinical Applications and Research, 10(3):248-254, 2015 (article)

DOI [BibTex]

DOI [BibTex]


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Identification of Time-Dependent Causal Model: A Gaussian Process Treatment

Huang, B., Zhang, K., Schölkopf, B.

In 24th International Joint Conference on Artificial Intelligence, Machine Learning Track, pages: 3561-3568, (Editors: Yang, Q. and Wooldridge, M.), AAAI Press, Palo Alto, California USA, IJCAI15, 2015 (inproceedings)

link (url) [BibTex]

link (url) [BibTex]


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Spatial statistics and attentional dynamics in scene viewing

Engbert, R., Trukenbrod, H., Barthelmé, S., Wichmann, F.

Journal of Vision, 15(1):1-17, 2015 (article)

Web PDF link (url) DOI Project Page [BibTex]

Web PDF link (url) DOI Project Page [BibTex]


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The Randomized Causation Coefficient

Lopez-Paz, D., Muandet, K., Recht, B.

Journal of Machine Learning, 16, pages: 2901-2907, 2015 (article)

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Towards denoising XMCD movies of fast magnetization dynamics using extended Kalman filter

Kopp, M., Harmeling, S., Schütz, G., Schölkopf, B., Fähnle, M.

Ultramicroscopy, 148, pages: 115-122, 2015 (article)

Abstract
The Kalman filter is a well-established approach to get information on the time-dependent state of a system from noisy observations. It was developed in the context of the Apollo project to see the deviation of the true trajectory of a rocket from the desired trajectory. Afterwards it was applied to many different systems with small numbers of components of the respective state vector (typically about 10). In all cases the equation of motion for the state vector was known exactly. The fast dissipative magnetization dynamics is often investigated by x-ray magnetic circular dichroism movies (XMCD movies), which are often very noisy. In this situation the number of components of the state vector is extremely large (about 105), and the equation of motion for the dissipative magnetization dynamics (especially the values of the material parameters of this equation) is not well known. In the present paper it is shown by theoretical considerations that – nevertheless – there is no principle problem for the use of the Kalman filter to denoise XMCD movies of fast dissipative magnetization dynamics.

Web DOI [BibTex]

Web DOI [BibTex]


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Multi-Source Domain Adaptation: A Causal View

Zhang, K., Gong, M., Schölkopf, B.

In Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, pages: 3150-3157, AAAI Press, AAAI, 2015 (inproceedings)

Web PDF link (url) [BibTex]

Web PDF link (url) [BibTex]


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Learning of Non-Parametric Control Policies with High-Dimensional State Features

van Hoof, H., Peters, J., Neumann, G.

In Proceedings of the 18th International Conference on Artificial Intelligence and Statistics, 38, pages: 995–1003, (Editors: Lebanon, G. and Vishwanathan, S.V.N. ), JMLR, AISTATS, 2015 (inproceedings)

link (url) [BibTex]

link (url) [BibTex]


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Artificial intelligence: Learning to see and act

Schölkopf, B.

Nature, News & Views, 518(7540):486-487, 2015 (article)

DOI [BibTex]

DOI [BibTex]


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Context affects lightness at the level of surfaces

Maertens, M., Wichmann, F., Shapley, R.

Journal of Vision, 15(1):1-15, 2015 (article)

Web PDF link (url) DOI [BibTex]

Web PDF link (url) DOI [BibTex]


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Towards a Learning Theory of Cause-Effect Inference

Lopez-Paz, D., Muandet, K., Schölkopf, B., Tolstikhin, I.

In Proceedings of the 32nd International Conference on Machine Learning, 37, pages: 1452–1461, JMLR Workshop and Conference Proceedings, (Editors: F. Bach and D. Blei), JMLR, ICML, 2015 (inproceedings)

Web Project Page [BibTex]

Web Project Page [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)

Web link (url) [BibTex]

Web link (url) [BibTex]


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Genome-wide analysis of local chromatin packing in Arabidopsis thaliana

Wang, C., Liu, C., Roqueiro, D., Grimm, D., Schwab, R., Becker, C., Lanz, C., Weigel, D.

Genome Research, 25(2):246-256, 2015 (article)

PDF DOI [BibTex]

PDF DOI [BibTex]


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BundleMAP: Anatomically Localized Features from dMRI for Detection of Disease

Khatami, M., Schmidt-Wilcke, T., Sundgren, P., Abbasloo, A., Schölkopf, B., Schultz, T.

In 6th International Workshop on Machine Learning in Medical Imaging, 9352, pages: 52-60, Lecture Notes in Computer Science, (Editors: L. Zhou, L. Wang, Q. Wang and Y. Shi), Springer, MLMI, 2015 (inproceedings)

DOI [BibTex]

DOI [BibTex]


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Hierarchical Label Queries with Data-Dependent Partitions

Kpotufe, S., Urner, R., Ben-David, S.

In Proceedings of the 28th Conference on Learning Theory, 40, pages: 1176-1189, (Editors: Grünwald, P. and Hazan, E. and Kale, S. ), JMLR, COLT, 2015 (inproceedings)

link (url) [BibTex]

link (url) [BibTex]


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Semi-Autonomous 3rd-Hand Robot

Lopes, M., Peters, J., Piater, J., Toussaint, M., Baisero, A., Busch, B., Erkent, O., Kroemer, O., Lioutikov, R., Maeda, G., Mollard, Y., Munzer, T., Shukla, D.

In Workshop on Cognitive Robotics in Future Manufacturing Scenarios, European Robotics Forum, 2015 (inproceedings)

link (url) [BibTex]

link (url) [BibTex]


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Assessment of brain tissue damage in the Sub-Acute Stroke Region by Multiparametric Imaging using [89-Zr]-Desferal-EPO-PET/MRI

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

World Molecular Imaging Conference, 2015 (talk)

[BibTex]

[BibTex]


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Statistical and Machine Learning Methods for Neuroimaging: Examples, Challenges, and Extensions to Diffusion Imaging Data

O’Donnell, L. J., Schultz, T.

In Visualization and Processing of Higher Order Descriptors for Multi-Valued Data, pages: 299-319, (Editors: Hotz, I. and Schultz, T.), Springer, 2015 (inbook)

Project Page [BibTex]

Project Page [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)

[BibTex]

[BibTex]


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Segmentation-based attenuation correction in positron emission tomography/magnetic resonance: erroneous tissue identification and its impact on positron emission tomography interpretation

Brendle, C., Schmidt, H., Oergel, A., Bezrukov, I., Mueller, M., Schraml, C., Pfannenberg, C., la Fougère, C., Nikolaou, K., Schwenzer, N.

Investigative Radiology, 50(5):339-346, 2015 (article)

DOI [BibTex]

DOI [BibTex]


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Discovering Temporal Causal Relations from Subsampled Data

Gong, M., Zhang, K., Schölkopf, B., Tao, D., Geiger, P.

In Proceedings of the 32nd International Conference on Machine Learning, 37, pages: 1898–1906, JMLR Workshop and Conference Proceedings, (Editors: F. Bach and D. Blei), JMLR, ICML, 2015 (inproceedings)

PDF link (url) [BibTex]

PDF link (url) [BibTex]


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Removing systematic errors for exoplanet search via latent causes

Schölkopf, B., Hogg, D., Wang, D., Foreman-Mackey, D., Janzing, D., Simon-Gabriel, C. J., Peters, J.

In Proceedings of The 32nd International Conference on Machine Learning, 37, pages: 2218–2226, JMLR Workshop and Conference Proceedings, (Editors: Bach, F. and Blei, D.), JMLR, ICML, 2015 (inproceedings)

Extended version on arXiv Web [BibTex]

Extended version on arXiv Web [BibTex]


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Active Nearest Neighbors in Changing Environments

Berlind, C., Urner, R.

In Proceedings of the 32nd International Conference on Machine Learning, 37, pages: 1870-1879, JMLR Workshop and Conference Proceedings, (Editors: Bach, F. and Blei, D. ), JMLR, ICML, 2015 (inproceedings)

link (url) [BibTex]

link (url) [BibTex]


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Active Reward Learning with a Novel Acquisition Function

Daniel, C., Kroemer, O., Viering, M., Metz, J., Peters, J.

Autonomous Robots, 39(3):389-405, 2015 (article)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Learning Inverse Dynamics Models with Contacts

Calandra, R., Ivaldi, S., Deisenroth, M., Rückert, E., Peters, J.

In IEEE International Conference on Robotics and Automation, pages: 3186-3191, ICRA, 2015 (inproceedings)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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A Probabilistic Framework for Semi-Autonomous Robots Based on Interaction Primitives with Phase Estimation

Maeda, G., Neumann, G., Ewerton, M., Lioutikov, R., Peters, J.

In Proceedings of the International Symposium of Robotics Research, ISRR, 2015 (inproceedings)

link (url) [BibTex]

link (url) [BibTex]


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Early time point in vivo PET/MR is a promising biomarker for determining efficacy of a novel Db(\alphaEGFR)-scTRAIL fusion protein therapy in a colon cancer model

Divine, M. R., Harant, M., Katiyar, P., Disselhorst, J. A., Bukala, D., Aidone, S., Siegemund, M., Pfizenmaier, K., Kontermann, R., Pichler, B. J.

World Molecular Imaging Conference, 2015 (talk)

[BibTex]

[BibTex]


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Neural Adaptive Sequential Monte Carlo

Gu, S., Ghahramani, Z., Turner, R. E.

Advances in Neural Information Processing Systems 28, pages: 2629-2637, (Editors: Corinna Cortes, Neil D. Lawrence, Daniel D. Lee, Masashi Sugiyama, and Roman Garnett), 29th Annual Conference on Neural Information Processing Systems (NIPS), 2015 (conference)

PDF Supplementary [BibTex]

PDF Supplementary [BibTex]


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Peer grading in a course on algorithms and data structures

Sajjadi, M. S. M., Alamgir, M., von Luxburg, U.

Workshop on Machine Learning for Education (ML4Ed) at the 32th International Conference on Machine Learning (ICML), 2015 (conference)

Arxiv [BibTex]

Arxiv [BibTex]


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A systematic search for transiting planets in the K2 data

Foreman-Mackey, D., Montet, B., Hogg, D., Morton, T., Wang, D., Schölkopf, B.

The Astrophysical Journal, 806(2), 2015 (article)

Abstract
Photometry of stars from the K2 extension of NASA’s Kepler mission is afflicted by systematic effects caused by small (few-pixel) drifts in the telescope pointing and other spacecraft issues. We present a method for searching K2 light curves for evidence of exoplanets by simultaneously fitting for these systematics and the transit signals of interest. This method is more computationally expensive than standard search algorithms but we demonstrate that it can be efficiently implemented and used to discover transit signals. We apply this method to the full Campaign 1 data set and report a list of 36 planet candidates transiting 31 stars, along with an analysis of the pipeline performance and detection efficiency based on artificial signal injections and recoveries. For all planet candidates, we present posterior distributions on the properties of each system based strictly on the transit observables.

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Causal Inference by Identification of Vector Autoregressive Processes with Hidden Components

Geiger, P., Zhang, K., Schölkopf, B., Gong, M., Janzing, D.

In Proceedings of the 32nd International Conference on Machine Learning, 37, pages: 1917–1925, JMLR Workshop and Conference Proceedings, (Editors: F. Bach and D. Blei), JMLR, ICML, 2015 (inproceedings)

PDF link (url) [BibTex]

PDF link (url) [BibTex]


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Brain-Computer Interfacing in Amyotrophic Lateral Sclerosis: Implications of a Resting-State EEG Analysis

Jayaram, V., Widmann, N., Förster, C., Fomina, T., Hohmann, M. R., Müller vom Hagen, J., Synofzik, M., Schölkopf, B., Schöls, L., Grosse-Wentrup, M.

In Proceedings of the 37th IEEE Conference for Engineering in Medicine and Biology, pages: 6979-6982, EMBC, 2015 (inproceedings)

PDF DOI [BibTex]

PDF DOI [BibTex]


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Identification of the Default Mode Network with Electroencephalography

Fomina, T., Hohmann, M. R., Schölkopf, B., Grosse-Wentrup, M.

In Proceedings of the 37th IEEE Conference for Engineering in Medicine and Biology, pages: 7566-7569, EMBC, 2015 (inproceedings)

DOI [BibTex]

DOI [BibTex]


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Towards Cognitive Brain-Computer Interfaces for Patients with Amyotrophic Lateral Sclerosis

Fomina, T., Schölkopf, B., Grosse-Wentrup, M.

In 7th Computer Science and Electronic Engineering Conference, pages: 77-80, Curran Associates, Inc., CEEC, 2015 (inproceedings)

DOI [BibTex]

DOI [BibTex]


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Learning Movement Primitive Attractor Goals and Sequential Skills from Kinesthetic Demonstrations

Manschitz, S., Kober, J., Gienger, M., Peters, J.

Robotics and Autonomous Systems, 74, Part A, pages: 97-107, 2015 (article)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Bayesian Optimization for Learning Gaits under Uncertainty

Calandra, R., Seyfarth, A., Peters, J., Deisenroth, M.

Annals of Mathematics and Artificial Intelligence, pages: 1-19, 2015 (article)

DOI [BibTex]

DOI [BibTex]


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Towards Learning Hierarchical Skills for Multi-Phase Manipulation Tasks

Kroemer, O., Daniel, C., Neumann, G., van Hoof, H., Peters, J.

In IEEE International Conference on Robotics and Automation, pages: 1503 - 1510, ICRA, 2015 (inproceedings)

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Probabilistic Line Searches for Stochastic Optimization

Mahsereci, M., Hennig, P.

In Advances in Neural Information Processing Systems 28, pages: 181-189, (Editors: C. Cortes, N.D. Lawrence, D.D. Lee, M. Sugiyama and R. Garnett), Curran Associates, Inc., 29th Annual Conference on Neural Information Processing Systems (NIPS), 2015 (inproceedings)

Abstract
In deterministic optimization, line searches are a standard tool ensuring stability and efficiency. Where only stochastic gradients are available, no direct equivalent has so far been formulated, because uncertain gradients do not allow for a strict sequence of decisions collapsing the search space. We construct a probabilistic line search by combining the structure of existing deterministic methods with notions from Bayesian optimization. Our method retains a Gaussian process surrogate of the univariate optimization objective, and uses a probabilistic belief over the Wolfe conditions to monitor the descent. The algorithm has very low computational cost, and no user-controlled parameters. Experiments show that it effectively removes the need to define a learning rate for stochastic gradient descent. [You can find the matlab research code under `attachments' below. The zip-file contains a minimal working example. The docstring in probLineSearch.m contains additional information. A more polished implementation in C++ will be published here at a later point. For comments and questions about the code please write to mmahsereci@tue.mpg.de.]

Matlab research code link (url) Project Page [BibTex]

Matlab research code link (url) Project Page [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)

[BibTex]

[BibTex]


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Assessment of murine brain tissue shrinkage caused by different histological fixatives using magnetic resonance and computed tomography imaging

Wehrl, H. F., Bezrukov, I., Wiehr, S., Lehnhoff, M., Fuchs, K., Mannheim, J. G., Quintanilla-Martinez, L., Kneilling, M., Pichler, B. J., Sauter, A. W.

Histology and Histopathology, 30(5):601-613, 2015 (article)

[BibTex]

[BibTex]


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Cosmology from Cosmic Shear with DES Science Verification Data

Abbott, T., Abdalla, F. B., Allam, S., Amara, A., Annis, J., Armstrong, R., Bacon, D., Banerji, M., Bauer, A. H., Baxter, E., others,

arXiv preprint arXiv:1507.05552, 2015 (techreport)

link (url) [BibTex]

link (url) [BibTex]


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BACKSHIFT: Learning causal cyclic graphs from unknown shift interventions

Rothenhäusler, D., Heinze, C., Peters, J., Meinshausen, N.

Advances in Neural Information Processing Systems 28, pages: 1513-1521, (Editors: C. Cortes, N.D. Lawrence, D.D. Lee, M. Sugiyama and R. Garnett), Curran Associates, Inc., 29th Annual Conference on Neural Information Processing Systems (NIPS), 2015 (conference)

link (url) [BibTex]

link (url) [BibTex]


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Particle Gibbs for Infinite Hidden Markov Models

Tripuraneni*, N., Gu*, S., Ge, H., Ghahramani, Z.

Advances in Neural Information Processing Systems 28, pages: 2395-2403, (Editors: Corinna Cortes, Neil D. Lawrence, Daniel D. Lee, Masashi Sugiyama, and Roman Garnett), 29th Annual Conference on Neural Information Processing Systems (NIPS), 2015, *equal contribution (conference)

PDF [BibTex]

PDF [BibTex]


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Improved Bayesian Information Criterion for Mixture Model Selection

Mehrjou, A., Hosseini, R., Araabi, B.

Pattern Recognition Letters, 69, pages: 22-27, 2015 (article)

DOI [BibTex]

DOI [BibTex]


Thumb xl 2016 peer grading
Peer grading in a course on algorithms and data structures

Sajjadi, M. S. M., Alamgir, M., von Luxburg, U.

Workshop on Crowdsourcing and Machine Learning (CrowdML) Workshop on Machine Learning for Education (ML4Ed) at at the 32th International Conference on Machine Learning (ICML), 2015 (conference)

Arxiv [BibTex]

Arxiv [BibTex]


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A Random Riemannian Metric for Probabilistic Shortest-Path Tractography

Hauberg, S., Schober, M., Liptrot, M., Hennig, P., Feragen, A.

In 18th International Conference on Medical Image Computing and Computer Assisted Intervention, 9349, pages: 597-604, Lecture Notes in Computer Science, MICCAI, 2015 (inproceedings)

PDF DOI [BibTex]

PDF DOI [BibTex]