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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)
ei
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)
ei
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
ei
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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Qiu, T., Palagi, S., Mark, A. G., Melde, K., Adams, F., Fischer, P.
Wireless actuation with functional acoustic surfaces
Appl. Phys. Lett., 109(19):191602, November 2016, APL Editor's pick. APL News. (article)
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Alarcon-Correa, M., Walker (Schamel), D., Qiu, T., Fischer, P.
Nanomotors
Eur. Phys. J.-Special Topics, 225(11-12):2241-2254, November 2016 (article)
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Palagi, S., Mark, A. G., Reigh, S. Y., Melde, K., Qiu, T., Zeng, H., Parmeggiani, C., Martella, D., Sanchez-Castillo, A., Kapernaum, N., Giesselmann, F., Wiersma, D. S., Lauga, E., Fischer, P.
Structured light enables biomimetic swimming and versatile locomotion of photoresponsive soft microrobots
Nature Materials, 15(6):647–653, November 2016, Max Planck press release, Nature News & Views. (article)
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Walker (Schamel), D., Singh, D. P., Fischer, P.
Capture of 2D Microparticle Arrays via a UV-Triggered Thiol-yne “Click” Reaction
Advanced Materials, 28(44):9846-9850, September 2016 (article)
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Jeong, H. H., Mark, A. G., Fischer, P.
Magnesium plasmonics for UV applications and chiral sensing
Chem. Comm., 52(82):12179-12182, September 2016 (article)
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Abdolmaleki, A., Lau, N., Reis, L., Peters, J., Neumann, G.
Contextual Policy Search for Linear and Nonlinear Generalization of a Humanoid Walking Controller
Journal of Intelligent & Robotic Systems, 83(3-4):393-408, (Editors: Luis Almeida, Lino Marques ), September 2016, Special Issue: Autonomous Robot Systems (article)
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Melde, K., Mark, A. G., Qiu, T., Fischer, P.
Holograms for acoustics
Nature, 537, pages: 518-522, September 2016, Max Planck press release, Nature News & Views, Nature Video. (article)
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Garbacz, P., Fischer, P., Kraemer, S.
A loop-gap resonator for chirality-sensitive nuclear magneto-electric resonance (NMER)
J. Chem. Phys., 145(10):104201, September 2016 (article)
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Jeong, H. H., Mark, A. G., Lee, T., Alarcon-Correa, M., Eslami, S., Qiu, T., Gibbs, J. G., Fischer, P.
Active Nanorheology with Plasmonics
Nano Letters, 16(8):4887-4894, July 2016 (article)
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Maeda, G., Ewerton, M., Koert, D., Peters, J.
Acquiring and Generalizing the Embodiment Mapping from Human Observations to Robot Skills
IEEE Robotics and Automation Letters, 1(2):784-791, July 2016 (article)
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Jeong, H. H., Mark, A. G., Alarcon-Correa, M., Kim, I., Oswald, P., Lee, T. C., Fischer, P.
Dispersion and shape engineered plasmonic nanosensors
Nature Communications, 7, pages: 11331, March 2016 (article)
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Zhang, K., Wang, Z., Zhang, J., Schölkopf, B.
On estimation of functional causal models: General results and application to post-nonlinear causal model
ACM Transactions on Intelligent Systems and Technologies, 7(2):article no. 13, January 2016 (article)
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Maier, A. M., Weig, C., Oswald, P., Frey, E., Fischer, P., Liedl, T.
Magnetic Propulsion of Microswimmers with DNA-Based Flagellar Bundles
Nano Letters, 16(2):906-910, January 2016 (article)
ei
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Klenske, E. D., Zeilinger, M., Schölkopf, B., Hennig, P.
Gaussian Process-Based Predictive Control for Periodic Error Correction
IEEE Transactions on Control Systems Technology , 24(1):110-121, 2016 (article)
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Townsend, J., Koep, N., Weichwald, S.
Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation
Journal of Machine Learning Research, 17(137):1-5, 2016 (article)
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Wang, D., Hogg, D. W., Foreman-Mackey, D., Schölkopf, B.
A Causal, Data-driven Approach to Modeling the Kepler Data
Publications of the Astronomical Society of the Pacific, 128(967):094503, 2016 (article)
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Daniel, C., van Hoof, H., Peters, J., Neumann, G.
Probabilistic Inference for Determining Options in Reinforcement Learning
Machine Learning, Special Issue, 104(2):337-357, (Editors: Gärtner, T., Nanni, M., Passerini, A. and Robardet, C.), European Conference on Machine Learning im Machine Learning, Journal Track, 2016, Best Student Paper Award of ECML-PKDD 2016 (article)
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Rothkegel, L. O. M., Trukenbrod, H. A., Schütt, H. H., Wichmann, F. A., Engbert, R.
Influence of initial fixation position in scene viewing
Vision Research, 129, pages: 33-49, 2016 (article)
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Wallis, T. S. A., Bethge, M., Wichmann, F. A.
Testing models of peripheral encoding using metamerism in an oddity paradigm
Journal of Vision, 16(2), 2016 (article)
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Schölkopf, B., Hogg, D., Wang, D., Foreman-Mackey, D., Janzing, D., Simon-Gabriel, C. J., Peters, J.
Modeling Confounding by Half-Sibling Regression
Proceedings of the National Academy of Science, 113(27):7391-7398, 2016 (article)
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Klenske, E. D., Hennig, P.
Dual Control for Approximate Bayesian Reinforcement Learning
Journal of Machine Learning Research, 17(127):1-30, 2016 (article)
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Divine, M. R., Katiyar, P., Kohlhofer, U., Quintanilla-Martinez, L., Disselhorst, J. A., Pichler, B. J.
A Population Based Gaussian Mixture Model Incorporating 18F-FDG-PET and DW-MRI Quantifies Tumor Tissue Classes
Journal of Nuclear Medicine, 57(3):473-479, 2016 (article)
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Seith, F., Gatidis, S., Schmidt, H., Bezrukov, I., la Fougère, C., Nikolaou, K., Pfannenberg, C., Schwenzer, N.
Comparison of Positron Emission Tomography Quantification Using Magnetic Resonance–and Computed Tomography–Based Attenuation Correction in Physiological Tissues and Lesions: A Whole-Body Positron Emission Tomography/Magnetic Resonance Study in 66 Patients
Investigative Radiology, 51(1):66-71, 2016 (article)
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Gomez Rodriguez, M., Song, L., Daneshmand, H., Schölkopf, B.
Estimating Diffusion Networks: Recovery Conditions, Sample Complexity and Soft-thresholding Algorithm
Journal of Machine Learning Research, 17(90):1-29, 2016 (article)
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Schütt, H. H., Harmeling, S., Macke, J. H., Wichmann, F. A.
Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data
Vision Research, 122, pages: 105-123, 2016 (article)
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Grosse-Wentrup, M., Janzing, D., Siegel, M., Schölkopf, B.
Identification of causal relations in neuroimaging data with latent confounders: An instrumental variable approach
NeuroImage, 125, pages: 825-833, 2016 (article)
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Daniel, C., Neumann, G., Kroemer, O., Peters, J.
Hierarchical Relative Entropy Policy Search
Journal of Machine Learning Research, 17(93):1-50, 2016 (article)
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Muandet, K., Sriperumbudur, B., Fukumizu, K., Gretton, A., Schölkopf, B.
Kernel Mean Shrinkage Estimators
Journal of Machine Learning Research, 17(48):1-41, 2016 (article)