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2016


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Contextual Policy Search for Linear and Nonlinear Generalization of a Humanoid Walking Controller

Abdolmaleki, A., Lau, N., Reis, L., Peters, J., Neumann, G.

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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DOI [BibTex]

2016


DOI [BibTex]


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Acquiring and Generalizing the Embodiment Mapping from Human Observations to Robot Skills

Maeda, G., Ewerton, M., Koert, D., Peters, J.

IEEE Robotics and Automation Letters, 1(2):784-791, July 2016 (article)

ei

DOI [BibTex]

DOI [BibTex]


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On estimation of functional causal models: General results and application to post-nonlinear causal model

Zhang, K., Wang, Z., Zhang, J., Schölkopf, B.

ACM Transactions on Intelligent Systems and Technologies, 7(2):article no. 13, January 2016 (article)

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PDF DOI [BibTex]

PDF DOI [BibTex]


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Gaussian Process-Based Predictive Control for Periodic Error Correction

Klenske, E. D., Zeilinger, M., Schölkopf, B., Hennig, P.

IEEE Transactions on Control Systems Technology , 24(1):110-121, 2016 (article)

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PDF DOI Project Page [BibTex]


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Modeling Confounding by Half-Sibling Regression

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

Proceedings of the National Academy of Science, 113(27):7391-7398, 2016 (article)

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Code link (url) DOI Project Page [BibTex]

Code link (url) DOI Project Page [BibTex]


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Dual Control for Approximate Bayesian Reinforcement Learning

Klenske, E. D., Hennig, P.

Journal of Machine Learning Research, 17(127):1-30, 2016 (article)

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PDF link (url) Project Page [BibTex]


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A Population Based Gaussian Mixture Model Incorporating 18F-FDG-PET and DW-MRI Quantifies Tumor Tissue Classes

Divine, M. R., Katiyar, P., Kohlhofer, U., Quintanilla-Martinez, L., Disselhorst, J. A., Pichler, B. J.

Journal of Nuclear Medicine, 57(3):473-479, 2016 (article)

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DOI [BibTex]

DOI [BibTex]


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Influence of initial fixation position in scene viewing

Rothkegel, L. O. M., Trukenbrod, H. A., Schütt, H. H., Wichmann, F. A., Engbert, R.

Vision Research, 129, pages: 33-49, 2016 (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Testing models of peripheral encoding using metamerism in an oddity paradigm

Wallis, T. S. A., Bethge, M., Wichmann, F. A.

Journal of Vision, 16(2), 2016 (article)

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DOI [BibTex]

DOI [BibTex]


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Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation

Townsend, J., Koep, N., Weichwald, S.

Journal of Machine Learning Research, 17(137):1-5, 2016 (article)

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PDF Arxiv Code Project page link (url) [BibTex]


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A Causal, Data-driven Approach to Modeling the Kepler Data

Wang, D., Hogg, D. W., Foreman-Mackey, D., Schölkopf, B.

Publications of the Astronomical Society of the Pacific, 128(967):094503, 2016 (article)

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link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


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Probabilistic Inference for Determining Options in Reinforcement Learning

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

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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DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Hierarchical Relative Entropy Policy Search

Daniel, C., Neumann, G., Kroemer, O., Peters, J.

Journal of Machine Learning Research, 17(93):1-50, 2016 (article)

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link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data

Schütt, H. H., Harmeling, S., Macke, J. H., Wichmann, F. A.

Vision Research, 122, pages: 105-123, 2016 (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Probabilistic Duality for Parallel Gibbs Sampling without Graph Coloring

Mescheder, L., Nowozin, S., Geiger, A.

Arxiv, 2016 (article)

Abstract
We present a new notion of probabilistic duality for random variables involving mixture distributions. Using this notion, we show how to implement a highly-parallelizable Gibbs sampler for weakly coupled discrete pairwise graphical models with strictly positive factors that requires almost no preprocessing and is easy to implement. Moreover, we show how our method can be combined with blocking to improve mixing. Even though our method leads to inferior mixing times compared to a sequential Gibbs sampler, we argue that our method is still very useful for large dynamic networks, where factors are added and removed on a continuous basis, as it is hard to maintain a graph coloring in this setup. Similarly, our method is useful for parallelizing Gibbs sampling in graphical models that do not allow for graph colorings with a small number of colors such as densely connected graphs.

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pdf [BibTex]


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γ‐Conicein und Coniin aus Geflecktem Schierling

Puidokait, M., Graefe, J., Sehl, A., Steinke, K., Siehl, H., Zeller, K., Sicker, D., Berger, S.

Chemie in unserer Zeit, 50(6):382-391, 2016 (article)

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DOI [BibTex]

DOI [BibTex]


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Kernel Mean Shrinkage Estimators

Muandet, K., Sriperumbudur, B., Fukumizu, K., Gretton, A., Schölkopf, B.

Journal of Machine Learning Research, 17(48):1-41, 2016 (article)

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link (url) Project Page [BibTex]


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Learning to Deblur

Schuler, C. J., Hirsch, M., Harmeling, S., Schölkopf, B.

IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(7):1439-1451, IEEE, 2016 (article)

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DOI [BibTex]

DOI [BibTex]


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Transfer Learning in Brain-Computer Interfaces

Jayaram, V., Alamgir, M., Altun, Y., Schölkopf, B., Grosse-Wentrup, M.

IEEE Computational Intelligence Magazine, 11(1):20-31, 2016 (article)

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PDF DOI [BibTex]

PDF DOI [BibTex]


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MERLiN: Mixture Effect Recovery in Linear Networks

Weichwald, S., Grosse-Wentrup, M., Gretton, A.

IEEE Journal of Selected Topics in Signal Processing, 10(7):1254-1266, 2016 (article)

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Arxiv Code PDF DOI [BibTex]

Arxiv Code PDF DOI [BibTex]


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Causal inference using invariant prediction: identification and confidence intervals

Peters, J., Bühlmann, P., Meinshausen, N.

Journal of the Royal Statistical Society, Series B (Statistical Methodology), 78(5):947-1012, 2016, (with discussion) (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Causal discovery and inference: concepts and recent methodological advances

Spirtes, P., Zhang, K.

Applied Informatics, 3(3):1-28, 2016 (article)

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DOI [BibTex]

DOI [BibTex]


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Self-regulation of brain rhythms in the precuneus: a novel BCI paradigm for patients with ALS

Fomina, T., Lohmann, G., Erb, M., Ethofer, T., Schölkopf, B., Grosse-Wentrup, M.

Journal of Neural Engineering, 13(6):066021, 2016 (article)

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link (url) [BibTex]

link (url) [BibTex]


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Influence Estimation and Maximization in Continuous-Time Diffusion Networks

Gomez-Rodriguez, M., Song, L., Du, N., Zha, H., Schölkopf, B.

ACM Transactions on Information Systems, 34(2):9:1-9:33, 2016 (article)

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DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Bootstrat: Population Informed Bootstrapping for Rare Variant Tests

Huang, H., Peloso, G. M., Howrigan, D., Rakitsch, B., Simon-Gabriel, C. J., Goldstein, J. I., Daly, M. J., Borgwardt, K., Neale, B. M.

bioRxiv, 2016, preprint (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Probabilistic Movement Models Show that Postural Control Precedes and Predicts Volitional Motor Control

Rueckert, E., Camernik, J., Peters, J., Babic, J.

Nature PG: Scientific Reports, 6(Article number: 28455), 2016 (article)

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DOI [BibTex]

DOI [BibTex]


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An overview of quantitative approaches in Gestalt perception

Jäkel, F., Singh, M., Wichmann, F. A., Herzog, M. H.

Vision Research, 126, pages: 3-8, 2016 (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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The population of long-period transiting exoplanets

Foreman-Mackey, D., Morton, T. D., Hogg, D. W., Agol, E., Schölkopf, B.

The Astronomical Journal, 152(6):206, 2016 (article)

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link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Learning Taxonomy Adaptation in Large-scale Classification

Babbar, R., Partalas, I., Gaussier, E., Amini, M., Amblard, C.

Journal of Machine Learning Research, 17(98):1-37, 2016 (article)

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link (url) [BibTex]

link (url) [BibTex]


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Recurrent Spiking Networks Solve Planning Tasks

Rueckert, E., Kappel, D., Tanneberg, D., Pecevski, D., Peters, J.

Nature PG: Scientific Reports, 6(Article number: 21142), 2016 (article)

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DOI [BibTex]

DOI [BibTex]


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Map-Based Probabilistic Visual Self-Localization

Brubaker, M. A., Geiger, A., Urtasun, R.

IEEE Trans. on Pattern Analysis and Machine Intelligence (PAMI), 2016 (article)

Abstract
Accurate and efficient self-localization is a critical problem for autonomous systems. This paper describes an affordable solution to vehicle self-localization which uses odometry computed from two video cameras and road maps as the sole inputs. The core of the method is a probabilistic model for which an efficient approximate inference algorithm is derived. The inference algorithm is able to utilize distributed computation in order to meet the real-time requirements of autonomous systems in some instances. Because of the probabilistic nature of the model the method is capable of coping with various sources of uncertainty including noise in the visual odometry and inherent ambiguities in the map (e.g., in a Manhattan world). By exploiting freely available, community developed maps and visual odometry measurements, the proposed method is able to localize a vehicle to 4m on average after 52 seconds of driving on maps which contain more than 2,150km of drivable roads.

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pdf Project Page [BibTex]

pdf Project Page [BibTex]


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BOiS—Berlin Object in Scene Database: Controlled Photographic Images for Visual Search Experiments with Quantified Contextual Priors

Mohr, J., Seyfarth, J., Lueschow, A., Weber, J. E., Wichmann, F. A., Obermayer, K.

Frontiers in Psychology, 2016 (article)

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DOI [BibTex]

DOI [BibTex]


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Preface to the ACM TIST Special Issue on Causal Discovery and Inference

Zhang, K., Li, J., Bareinboim, E., Schölkopf, B., Pearl, J.

ACM Transactions on Intelligent Systems and Technologies, 7(2):article no. 17, 2016 (article)

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DOI [BibTex]

DOI [BibTex]


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Ab initio theory for ultrafast magnetization dynamics with a dynamic band structure

Müller, B. Y., Haag, M., Fähnle, M.

{Journal of Magnetism and Magnetic Materials}, 414, pages: 14-18, North-Holland, Amsterdam, 2016 (article)

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DOI [BibTex]

DOI [BibTex]


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High-resolution analysis of currents at low-angle grain boundaries in YBCO thin films using magnetooptics and magnetic x-ray microscopy

Ruoß, S., Stahl, C., Bayer, J., Schütz, G., Albrecht, J., Laviano, F.

{IEEE Transactions on Applied Superconductivity}, 26(3), IEEE, New York, NY, 2016 (article)

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DOI [BibTex]

DOI [BibTex]


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Three-dimensional character of the magnetization dynamics in magnetic vortex structures: Hybridization of flexure gyromodes with spin waves

Noske, M., Stoll, H., Fähnle, M., Gangwar, A., Woltersdorf, G., Slavin, A., Weigand, M., Dieterle, G., Förster, J., Back, C. H., Schütz, G.

{Physical Review Letters}, 117(3), American Physical Society, Woodbury, N.Y., 2016 (article)

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DOI [BibTex]

DOI [BibTex]


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Coercivity scaling in antidot lattices in Fe, Ni, and NiFe thin films

Gräfe, J., Schütz, G., Goering, E. J.

{Journal of Magnetism and Magnetic Materials}, 419, pages: 517-520, North-Holland, Amsterdam, 2016 (article)

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DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Nanostructured materials for solid-state hydrogen storage: A review of the achievement of COST Action MP1103

Callini, E., Aguey-Zinsou, K., Ahuja, R., Ares, J. R., Bals, S., Biliskov, N., Chakraborty, S., Charalambopoulou, G., Chaudhary, A., Cuevas, F., Dam, B., de Jongh, P., Dornheim, M., Filinchuk, Y., Grbovic-Novakovic, J., Hirscher, M., Jensen, T. R., Jensen, P. B., Novakovic, N., Lai, Q., Leardini, F., Gattia, D. M., Pasquini, L., Steriotis, T., Turner, S., Vegge, T., Züttel, A., Montone, A.

{International Journal of Hydrogen Energy}, 41(32):14404-14428, Elsevier, Amsterdam, 2016 (article)

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DOI [BibTex]

DOI [BibTex]


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Magnetic X-ray microscopy at low temperatures - Visualization of flux distributions in superconductors

Stahl, C., Ruoß, S., Weigand, M., Bechtel, M., Schütz, G., Albrecht, J.

{AIP Conference Proceedings}, 1696, AIP Publishing, Melville, NY, 2016 (article)

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DOI [BibTex]

DOI [BibTex]


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Enhanced non-adiabaticity in vortex cores due to the emergent Hall effect

Bisig, A., Akosa, C. A., Moon, J., Rhensius, J., Moutafis, C., von Bieren, A., Heidler, J., Kiliani, G., Kammerer, M., Curcic, M., Weigand, M., Tyliszczak, T., Van Waeyenberge, B., Stoll, H., Schütz, G., Lee, K., Manchon, A., Kläui, M.

{Physical Review Letters}, 117(27), American Physical Society, Woodbury, N.Y., 2016 (article)

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DOI [BibTex]

DOI [BibTex]


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Quantitative magneto-optical analysis of the role of finite temperatures on the critical state in YBCO thin films

Albrecht, J., Brück, S., Stahl, C., Ruoß, S.

{Superconductor Science and Technology}, 29(11), IOP Pub., Bristol, 2016 (article)

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DOI [BibTex]

DOI [BibTex]


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Bio-inspired feedback-circuit implementation of discrete, free energy optimizing, winner-take-all computations

Genewein, T, Braun, DA

Biological Cybernetics, 110(2):135–150, June 2016 (article)

Abstract
Bayesian inference and bounded rational decision-making require the accumulation of evidence or utility, respectively, to transform a prior belief or strategy into a posterior probability distribution over hypotheses or actions. Crucially, this process cannot be simply realized by independent integrators, since the different hypotheses and actions also compete with each other. In continuous time, this competitive integration process can be described by a special case of the replicator equation. Here we investigate simple analog electric circuits that implement the underlying differential equation under the constraint that we only permit a limited set of building blocks that we regard as biologically interpretable, such as capacitors, resistors, voltage-dependent conductances and voltage- or current-controlled current and voltage sources. The appeal of these circuits is that they intrinsically perform normalization without requiring an explicit divisive normalization. However, even in idealized simulations, we find that these circuits are very sensitive to internal noise as they accumulate error over time. We discuss in how far neural circuits could implement these operations that might provide a generic competitive principle underlying both perception and action.

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DOI [BibTex]

DOI [BibTex]


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Collective modes in three-dimensional magnonic vortex crystals

Hänze, M., Adolff, C. F., Schulte, B., Möller, J., Weigand, M., Meier, G.

{Scientific Reports}, 6, Nature Publishing Group, London, UK, 2016 (article)

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DOI [BibTex]

DOI [BibTex]


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Spin wave mediated unidirectional vortex core reversal by two orthogonal monopolar field pulses: The essential role of three-dimensional magnetization dynamics

Noske, M., Stoll, H., Fähnle, M., Gangwar, A., Woltersdorf, G., Slavin, A., Weigand, M., Dieterle, G., Förster, J., Back, C. H., Schütz, G.

{Journal of Applied Physics}, 119(17), AIP Publishing, New York, NY, 2016 (article)

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DOI [BibTex]

DOI [BibTex]


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Magnetic vortex cores as tunable spin-wave emitters

Wintz, S., Tiberkevich, V., Weigand, M., Raabe, J., Lindner, J., Erbe, A., Slavin, A., Fassbender, J.

{Nature Nanotechnology}, 11(11):948-953, Nature Publishing Group, London, 2016 (article)

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DOI [BibTex]

DOI [BibTex]