Header logo is


2016


Thumb xl amjadi et al 2016 advanced functional materials
Stretchable, Skin-Mountable, and Wearable Strain Sensors and Their Potential Applications: A Review

Amjadi, M., Kyung, K., Park, I., Sitti, M.

Advanced Functional Materials, 26, pages: 1678-1698, Febuary 2016 (article)

Abstract
There is a growing demand for flexible and soft electronic devices. In particular, stretchable, skin-mountable, and wearable strain sensors are needed for several potential applications including personalized health-monitoring, human motion detection, human-machine interfaces, soft robotics, and so forth. This Feature Article presents recent advancements in the development of flexible and stretchable strain sensors. The article shows that highly stretchable strain sensors are successfully being developed by new mechanisms such as disconnection between overlapped nanomaterials, crack propagation in thin films, and tunneling effect, different from traditional strain sensing mechanisms. Strain sensing performances of recently reported strain sensors are comprehensively studied and discussed, showing that appropriate choice of composite structures as well as suitable interaction between functional nanomaterials and polymers are essential for the high performance strain sensing. Next, simulation results of piezoresistivity of stretchable strain sensors by computational models are reported. Finally, potential applications of flexible strain sensors are described. This survey reveals that flexible, skin-mountable, and wearable strain sensors have potential in diverse applications while several grand challenges have to be still overcome.

pi

DOI [BibTex]

2016


DOI [BibTex]


Thumb xl b 07384529
Size optimization of a magnetic system for drug delivery with capsule robots

Munoz, F., Alici, G., Li, W., Sitti, M.

IEEE Transactions on Magnetics, 52(5):1-11, IEEE, January 2016 (article)

Abstract
In this paper, we present a methodology for the size optimization of an external magnetic system made of arc-shaped permanent magnets (ASMs). This magnetic system is able to remotely actuate a drug-release module embedded in a prototype of a capsule robot. The optimization of the magnetic system is carried out by using an accurate analytical model that is valid for any arbitrary dimensions of the ASMs. By using this analytical model, we perform parametric studies and conduct a statistical analysis [analysis of variance (ANOVA)] to investigate efficient ways to distribute the volume of the ASMs so that the dimensions and volume of the magnetic system are minimized while optimal flux densities and magnetic torques are obtained to actuate the drug delivery system (DDS). The ANOVA results, at 5% significance level, indicate that changes in the angular width followed by changes in the length of the ASMs have the highest impact on the magnetic linkage. Furthermore, our experimental results, which are in agreement with the analytical results, show that the size optimization of the magnetic system is effective for the actuation of the DDS in capsule robots.

pi

DOI [BibTex]

DOI [BibTex]


no image
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)

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


Thumb xl toc image
Magnetic Propulsion of Microswimmers with DNA-Based Flagellar Bundles

Maier, A. M., Weig, C., Oswald, P., Frey, E., Fischer, P., Liedl, T.

Nano Letters, 16(2):906-910, January 2016 (article)

Abstract
We show that DNA-based self-assembly can serve as a general and flexible tool to construct artificial flagella of several micrometers in length and only tens of nanometers in diameter. By attaching the DNA flagella to biocompatible magnetic microparticles, we provide a proof of concept demonstration of hybrid structures that, when rotated in an external magnetic field, propel by means of a flagellar bundle, similar to self-propelling peritrichous bacteria. Our theoretical analysis predicts that flagellar bundles that possess a length-dependent bending stiffness should exhibit a superior swimming speed compared to swimmers with a single appendage. The DNA self-assembly method permits the realization of these improved flagellar bundles in good agreement with our quantitative model. DNA flagella with well-controlled shape could fundamentally increase the functionality of fully biocompatible nanorobots and extend the scope and complexity of active materials.

pf

DOI [BibTex]

DOI [BibTex]


Thumb xl teaser web
Human Pose Estimation from Video and IMUs

Marcard, T. V., Pons-Moll, G., Rosenhahn, B.

Transactions on Pattern Analysis and Machine Intelligence PAMI, 38(8):1533-1547, January 2016 (article)

ps

data pdf dataset_documentation [BibTex]

data pdf dataset_documentation [BibTex]


Thumb xl cloud tracking
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)

ei pn

PDF DOI [BibTex]

PDF DOI [BibTex]


no image
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)

ei

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


no image
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)

ei

link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


no image
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)

am ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


Thumb xl weak supervision
Weak Supervision for Detecting Object Classes from Activities

Srikantha, A., Gall, J.

Computer Vision and Image Understanding (CVIU), Elsevier, 2016 (article) In press

elsevier preprint link (url) DOI [BibTex]

elsevier preprint link (url) DOI [BibTex]


no image
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)

ei

link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


no image
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)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


no image
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)

ei

Code link (url) DOI Project Page [BibTex]

Code link (url) DOI Project Page [BibTex]


Thumb xl dual control sampled b
Dual Control for Approximate Bayesian Reinforcement Learning

Klenske, E. D., Hennig, P.

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

ei pn

PDF link (url) [BibTex]

PDF link (url) [BibTex]


no image
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)

ei

DOI [BibTex]

DOI [BibTex]


Thumb xl siyong
Shape estimation of subcutaneous adipose tissue using an articulated statistical shape model

Yeo, S. Y., Romero, J., Loper, M., Machann, J., Black, M.

Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization, 0(0):1-8, 2016 (article)

ps

publisher website preprint pdf link (url) DOI Project Page [BibTex]

publisher website preprint pdf link (url) DOI Project Page [BibTex]


Thumb xl img02
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.

avg

pdf [BibTex]


no image
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)

ei

link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


no image
Hierarchical Relative Entropy Policy Search

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

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

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


no image
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)

mms

DOI [BibTex]

DOI [BibTex]


no image
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)

ei

link (url) [BibTex]

link (url) [BibTex]


no image
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)

ei

DOI [BibTex]

DOI [BibTex]


no image
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)

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


no image
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)

ei

Arxiv Code PDF DOI Project Page [BibTex]

Arxiv Code PDF DOI Project Page [BibTex]


no image
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)

ei

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Causal discovery and inference: concepts and recent methodological advances

Spirtes, P., Zhang, K.

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

ei

DOI [BibTex]

DOI [BibTex]


no image
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)

ei

link (url) Project Page [BibTex]


no image
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)

ei

DOI Project Page Project Page [BibTex]

DOI Project Page Project Page [BibTex]


no image
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)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


no image
Event-based Sampling for Reducing Communication Load in Realtime Human Motion Analysis by Wireless Inertial Sensor Networks

Laidig, D., Trimpe, S., Seel, T.

Current Directions in Biomedical Engineering, 2(1):711-714, De Gruyter, 2016 (article)

am ics

PDF DOI [BibTex]

PDF DOI [BibTex]


no image
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)

ei

link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


no image
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)

ei

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
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)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


no image
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)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


Thumb xl screen shot 2016 02 22 at 11.46.41
The GRASP Taxonomy of Human Grasp Types

Feix, T., Romero, J., Schmiedmayer, H., Dollar, A., Kragic, D.

Human-Machine Systems, IEEE Transactions on, 46(1):66-77, 2016 (article)

ps

publisher website pdf DOI Project Page [BibTex]

publisher website pdf DOI Project Page [BibTex]


no image
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)

ei

DOI [BibTex]

DOI [BibTex]


no image
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)

ei

DOI [BibTex]

DOI [BibTex]


Thumb xl pami
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.

avg ps

pdf Project Page [BibTex]

pdf Project Page [BibTex]


no image
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)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


no image
Momentum Control with Hierarchical Inverse Dynamics on a Torque-Controlled Humanoid

Herzog, A., Rotella, N., Mason, S., Grimminger, F., Schaal, S., Righetti, L.

Autonomous Robots, 40(3):473-491, 2016 (article)

Abstract
Hierarchical inverse dynamics based on cascades of quadratic programs have been proposed for the control of legged robots. They have important benefits but to the best of our knowledge have never been implemented on a torque controlled humanoid where model inaccuracies, sensor noise and real-time computation requirements can be problematic. Using a reformulation of existing algorithms, we propose a simplification of the problem that allows to achieve real-time control. Momentum-based control is integrated in the task hierarchy and a LQR design approach is used to compute the desired associated closed-loop behavior and improve performance. Extensive experiments on various balancing and tracking tasks show very robust performance in the face of unknown disturbances, even when the humanoid is standing on one foot. Our results demonstrate that hierarchical inverse dynamics together with momentum control can be efficiently used for feedback control under real robot conditions.

am mg

link (url) DOI [BibTex]


no image
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)

mms

DOI [BibTex]

DOI [BibTex]


no image
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)

mms

DOI [BibTex]

DOI [BibTex]


no image
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)

mms

DOI [BibTex]

DOI [BibTex]


no image
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)

mms

DOI Project Page [BibTex]

DOI Project Page [BibTex]


no image
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)

mms

DOI [BibTex]

DOI [BibTex]