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Ma, Z., Holle, A., Melde, K., Qiu, T., Poeppel, K., Kadiri, V., Fischer, P.
Acoustic Holographic Cell Patterning in a Biocompatible Hydrogel
Adv. Mat., October 2019 (article)
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Choi, E., Adams, F., Gengenbacher, A., Schlager, D., Palagi, S., Müller, P., Wetterauer, U., Miernik, A., Fischer, P., Qiu, T.
A High-Fidelity Phantom for the Simulation and Quantitative Evaluation of Transurethral Resection of the Prostate
Annals of Biomed. Eng., October 2019 (article)
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Fischer, P.
Interactive Materials – Drivers of Future Robotic Systems
Adv. Mat., October 2019 (article)
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Jeong, H., Adams, M. C., Guenther, J., Alarcon-Correa, M., Kim, I., Choi, E., Miksch, C., Mark, A. F. M., Mark, A. G., Fischer, P.
Arrays of plasmonic nanoparticle dimers with defined nanogap spacers
ACS Nano, September 2019 (article)
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Gebhard, T., Kilbertus, N., Harry, I., Schölkopf, B.
Convolutional neural networks: A magic bullet for gravitational-wave detection?
Physical Review D, 100(6):063015, American Physical Society, September 2019 (article)
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Babbar, R., Schölkopf, B.
Data scarcity, robustness and extreme multi-label classification
Machine Learning, 108(8):1329-1351, September 2019, Special Issue of the ECML PKDD 2019 Journal Track (article)
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Kadiri, V. M., Alarcon-Correa, M., Guenther, J. P., Ruppert, J., Bill, J., Rothenstein, D., Fischer, P.
Genetically modified M13 bacteriophage nanonets for enzyme catalysis and recovery
Catalysts, 9, pages: 723, August 2019 (article)
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Palagi, S., Singh, D. P., Fischer, P.
Light-controlled micromotors and soft microrobots
Adv. Opt. Mat., 7, pages: 1900370, August 2019 (article)
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Alarcon-Correa, M., Guenther, J., Troll, J., Kadiri, V. M., Bill, J., Fischer, P., Rothenstein, D.
Self-Assembled Phage-Based Colloids for High Localized Enzymatic Activity
ACS Nano, March 2019 (article)
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Guenther, J., Majer, G., Fischer, P.
Absolute diffusion measurements of active enzyme solutions by NMR
J. Chem. Phys., 150(124201), March 2019 (article)
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Choudhury, U., Singh, D. P., Qiu, T., Fischer, P.
Chemical Nanomotors at the Gram Scale Form a Dense Active Optorheological Medium
Adv. Mat., (1807382), Febuary 2019 (article)
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Collins, J., Rusimova, K., Hooper, D., Jeong, H. H., Ohnoutek, L., Pradaux-Caggiano, F., Verbiest, T., Carbery, D., Fischer, P., Valev, V.
First Observation of Optical Activity in Hyper-Rayleigh Scattering
Phys. Rev. X, 9(011024), January 2019 (article)
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Aghaeifar, A., Zhou, J., Heule, R., Tabibian, B., Schölkopf, B., Jia, F., Zaitsev, M., Scheffler, K.
A 32-channel multi-coil setup optimized for human brain shimming at 9.4T
Magnetic Resonance in Medicine, 2019, (Early View) (article)
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Stimper, V., Bauer, S., Ernstorfer, R., Schölkopf, B., Xian, R. P.
Multidimensional Contrast Limited Adaptive Histogram Equalization
IEEE Access, 7, pages: 165437-165447, 2019 (article)
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Tabibian, B., Upadhyay, U., De, A., Zarezade, A., Schölkopf, B., Gomez Rodriguez, M.
Enhancing Human Learning via Spaced Repetition Optimization
Proceedings of the National Academy of Sciences, 2019, PNAS published ahead of print January 22, 2019 (article)
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Büchler, D., Calandra, R., Peters, J.
Learning to Control Highly Accelerated Ballistic Movements on Muscular Robots
2019 (article) Submitted
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Runge, J., Bathiany, S., Bollt, E., Camps-Valls, G., Coumou, D., Deyle, E., Glymour, C., Kretschmer, M., Mahecha, M., van Nes, E., Peters, J., Quax, R., Reichstein, M., Scheffer, M. S. B., Spirtes, P., Sugihara, G., Sun, J., Zhang, K., Zscheischler, J.
Inferring causation from time series with perspectives in Earth system sciences
Nature Communications, 2019 (article) In revision
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Kübler, J. M., Muandet, K., Schölkopf, B.
Quantum mean embedding of probability distributions
Physical Review Research, 1(3):033159, American Physical Society, 2019 (article)
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Gomez-Gonzalez, S., Nemmour, Y., Schölkopf, B., Peters, J.
Reliable Real-Time Ball Tracking for Robot Table Tennis
Robotics, 8(4):90, 2019 (article)
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Koc, O., Maeda, G., Peters, J.
Optimizing the Execution of Dynamic Robot Movements With Learning Control
IEEE Transactions on Robotics, pages: 1-16, 2019 (article)
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Koc, O., Peters, J.
Learning to Serve: An Experimental Study for a New Learning From Demonstrations Framework
IEEE Robotics and Automation Letters, 4(2):1784-1791, 2019 (article)
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Klus, S., Schuster, I., Muandet, K.
Eigendecompositions of Transfer Operators in Reproducing Kernel Hilbert Spaces
Journal of Nonlinear Science, 2019, First Online: 21 August 2019 (article)
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Schmidt, H., Brendle, C., Schraml, C., Martirosian, P., Bezrukov, I., Hetzel, J., Müller, M., Sauter, A., Claussen, C., Pfannenberg, C., Schwenzer, N.
Correlation of Simultaneously Acquired Diffusion-Weighted Imaging and 2-Deoxy-[18F] fluoro-2-D-glucose Positron Emission Tomography of Pulmonary Lesions in a Dedicated Whole-Body Magnetic Resonance/Positron Emission Tomography System
Investigative Radiology, 48(5):247-255, May 2013 (article)
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Lemeire, J., Janzing, D.
Replacing Causal Faithfulness with Algorithmic Independence of Conditionals
Minds and Machines, 23(2):227-249, May 2013 (article)
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Balduzzi, D., Tononi, G.
What can neurons do for their brain? Communicate selectivity with bursts
Theory in Biosciences , 132(1):27-39, Springer, March 2013 (article)
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Boularias, A., Chaib-draa, B.
Apprenticeship Learning with Few Examples
Neurocomputing, 104, pages: 83-96, March 2013 (article)
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Hennig, P., Kiefel, M.
Quasi-Newton Methods: A New Direction
Journal of Machine Learning Research, 14(1):843-865, March 2013 (article)
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Cavusoglu, M., Pohmann, R., Burger, H. C., Uludag, K.
Regional effects of magnetization dispersion on quantitative perfusion imaging for pulsed and continuous arterial spin labeling
Magnetic Resonance in Medicine, 69(2):524-530, Febuary 2013 (article)
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Sra, S., Karp, D.
The multivariate Watson distribution: Maximum-likelihood estimation and other aspects
Journal of Multivariate Analysis, 114, pages: 256-269, February 2013 (article)
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Maier, M., von Luxburg, U., Hein, M.
How the result of graph clustering methods depends on the construction of the graph
ESAIM: Probability & Statistics, 17, pages: 370-418, January 2013 (article)
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Sra, S.
Explicit eigenvalues of certain scaled trigonometric matrices
Linear Algebra and its Applications, 438(1):173-181, January 2013 (article)
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Gerhard, H., Wichmann, F., Bethge, M.
How Sensitive Is the Human Visual System to the Local Statistics of Natural Images?
PLoS Computational Biology, 9(1):e1002873, January 2013 (article)
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Goris, R., Putzeys, T., Wagemans, J., Wichmann, F.
A neural population model for visual pattern detection
Psychological Review, 120(3):472–496, 2013 (article)
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Grosse-Wentrup, M., Schölkopf, B.
A Review of Performance Variations in SMR-Based Brain–Computer Interfaces (BCIs)
In Brain-Computer Interface Research, pages: 39-51, 4, SpringerBriefs in Electrical and Computer Engineering, (Editors: Guger, C., Allison, B. Z. and Edlinger, G.), Springer, 2013 (inbook)
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Grimm, D., Hagmann, J., Koenig, D., Weigel, D., Borgwardt, KM.
Accurate indel prediction using paired-end short reads
BMC Genomics, 14(132), 2013 (article)
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Bottou, L., Peters, J., Quiñonero-Candela, J., Charles, D., Chickering, D., Portugualy, E., Ray, D., Simard, P., Snelson, E.
Counterfactual Reasoning and Learning Systems: The Example of Computational Advertising
Journal of Machine Learning Research, 14, pages: 3207-3260, 2013 (article)
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Maertens, M., Wichmann, F.
When luminance increment thresholds depend on apparent lightness
Journal of Vision, 13(6):1-11, 2013 (article)
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Azencott, C., Grimm, D., Sugiyama, M., Kawahara, Y., Borgwardt, K.
Efficient network-guided multi-locus association mapping with graph cuts
Bioinformatics, 29(13):i171-i179, 2013 (article)
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Schölkopf, B., Janzing, D., Peters, J., Sgouritsa, E., Zhang, K., Mooij, J.
Semi-supervised learning in causal and anticausal settings
In Empirical Inference, pages: 129-141, 13, Festschrift in Honor of Vladimir Vapnik, (Editors: Schölkopf, B., Luo, Z. and Vovk, V.), Springer, 2013 (inbook)
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Janzing, D., Balduzzi, D., Grosse-Wentrup, M., Schölkopf, B.
Quantifying causal influences
Annals of Statistics, 41(5):2324-2358, 2013 (article)
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Wang, Z., Mülling, K., Deisenroth, M., Ben Amor, H., Vogt, D., Schölkopf, B., Peters, J.
Probabilistic movement modeling for intention inference in human-robot interaction
International Journal of Robotics Research, 32(7):841-858, 2013 (article)
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Loktyushin, A., Nickisch, H., Pohmann, R., Schölkopf, B.
Blind Retrospective Motion Correction of MR Images
Magnetic Resonance in Medicine (MRM), 70(6):1608–1618, 2013 (article)
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Barthelmé, S., Trukenbrod, H., Engbert, R., Wichmann, F.
Modeling fixation locations using spatial point processes
Journal of Vision, 13(12):1-34, 2013 (article)
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Sra, S.
Tractable large-scale optimization in machine learning
In Tractability: Practical Approaches to Hard Problems, pages: 202-230, 7, (Editors: Bordeaux, L., Hamadi , Y., Kohli, P. and Mateescu, R. ), Cambridge University Press , 2013 (inbook)
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Mechelke, M., Habeck, M.
A probabilistic model for secondary structure prediction from protein chemical shifts
Proteins: Structure, Function, and Bioinformatics, 81(6):984–993, 2013 (article)
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Reichstein, M., Bahn, M., Ciais, P., Frank, D., Mahecha, M., Seneviratne, S., Zscheischler, J., Beer, C., Buchmann, N., Frank, D., Papale, D., Rammig, A., Smith, P., Thonicke, K., van der Velde, M., Vicca, S., Walz, A., Wattenbach, M.
Climate Extremes and the Carbon Cycle
Nature, 500, pages: 287-295, 2013 (article)
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Schönfelder, V., Wichmann, F.
Identification of stimulus cues in narrow-band tone-in-noise detection using sparse observer models
Journal of the Acoustical Society of America, 134(1):447-463, 2013 (article)
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Englert, P., Paraschos, A., Peters, J., Deisenroth, M.
Probabilistic Model-based Imitation Learning
Adaptive Behavior Journal, 21(5):388-403, 2013 (article)
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Balduzzi, D., Ortega, P., Besserve, M.
Metabolic cost as an organizing principle for cooperative learning
Advances in Complex Systems, 16(02n03):1350012, 2013 (article)
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Bezrukov, I., Mantlik, F., Schmidt, H., Schölkopf, B., Pichler, B.
MR-based PET Attenuation Correction for PET/MR Imaging
Seminars in Nuclear Medicine, 43(1):45-59, 2013 (article)