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2018


A Value-Driven Eldercare Robot: Virtual and Physical Instantiations of a Case-Supported Principle-Based Behavior Paradigm
A Value-Driven Eldercare Robot: Virtual and Physical Instantiations of a Case-Supported Principle-Based Behavior Paradigm

Anderson, M., Anderson, S., Berenz, V.

Proceedings of the IEEE, pages: 1,15, October 2018 (article)

Abstract
In this paper, a case-supported principle-based behavior paradigm is proposed to help ensure ethical behavior of autonomous machines. We argue that ethically significant behavior of autonomous systems should be guided by explicit ethical principles determined through a consensus of ethicists. Such a consensus is likely to emerge in many areas in which autonomous systems are apt to be deployed and for the actions they are liable to undertake. We believe that this is the case since we are more likely to agree on how machines ought to treat us than on how human beings ought to treat one another. Given such a consensus, particular cases of ethical dilemmas where ethicists agree on the ethically relevant features and the right course of action can be used to help discover principles that balance these features when they are in conflict. Such principles not only help ensure ethical behavior of complex and dynamic systems but also can serve as a basis for justification of this behavior. The requirements, methods, implementation, and evaluation components of the paradigm are detailed as well as its instantiation in both a simulated and real robot functioning in the domain of eldercare.

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link (url) DOI [BibTex]

2018



Playful: Reactive Programming for Orchestrating Robotic Behavior
Playful: Reactive Programming for Orchestrating Robotic Behavior

Berenz, V., Schaal, S.

IEEE Robotics Automation Magazine, 25(3):49-60, September 2018 (article) In press

Abstract
For many service robots, reactivity to changes in their surroundings is a must. However, developing software suitable for dynamic environments is difficult. Existing robotic middleware allows engineers to design behavior graphs by organizing communication between components. But because these graphs are structurally inflexible, they hardly support the development of complex reactive behavior. To address this limitation, we propose Playful, a software platform that applies reactive programming to the specification of robotic behavior.

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playful website playful_IEEE_RAM link (url) DOI [BibTex]


ClusterNet: Instance Segmentation in RGB-D Images
ClusterNet: Instance Segmentation in RGB-D Images

Shao, L., Tian, Y., Bohg, J.

arXiv, September 2018, Submitted to ICRA'19 (article) Submitted

Abstract
We propose a method for instance-level segmentation that uses RGB-D data as input and provides detailed information about the location, geometry and number of {\em individual\/} objects in the scene. This level of understanding is fundamental for autonomous robots. It enables safe and robust decision-making under the large uncertainty of the real-world. In our model, we propose to use the first and second order moments of the object occupancy function to represent an object instance. We train an hourglass Deep Neural Network (DNN) where each pixel in the output votes for the 3D position of the corresponding object center and for the object's size and pose. The final instance segmentation is achieved through clustering in the space of moments. The object-centric training loss is defined on the output of the clustering. Our method outperforms the state-of-the-art instance segmentation method on our synthesized dataset. We show that our method generalizes well on real-world data achieving visually better segmentation results.

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link (url) [BibTex]

link (url) [BibTex]


Real-time Perception meets Reactive Motion Generation
Real-time Perception meets Reactive Motion Generation

(Best Systems Paper Finalists - Amazon Robotics Best Paper Awards in Manipulation)

Kappler, D., Meier, F., Issac, J., Mainprice, J., Garcia Cifuentes, C., Wüthrich, M., Berenz, V., Schaal, S., Ratliff, N., Bohg, J.

IEEE Robotics and Automation Letters, 3(3):1864-1871, July 2018 (article)

Abstract
We address the challenging problem of robotic grasping and manipulation in the presence of uncertainty. This uncertainty is due to noisy sensing, inaccurate models and hard-to-predict environment dynamics. Our approach emphasizes the importance of continuous, real-time perception and its tight integration with reactive motion generation methods. We present a fully integrated system where real-time object and robot tracking as well as ambient world modeling provides the necessary input to feedback controllers and continuous motion optimizers. Specifically, they provide attractive and repulsive potentials based on which the controllers and motion optimizer can online compute movement policies at different time intervals. We extensively evaluate the proposed system on a real robotic platform in four scenarios that exhibit either challenging workspace geometry or a dynamic environment. We compare the proposed integrated system with a more traditional sense-plan-act approach that is still widely used. In 333 experiments, we show the robustness and accuracy of the proposed system.

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arxiv video video link (url) DOI Project Page [BibTex]


Learning 3D Shape Completion under Weak Supervision
Learning 3D Shape Completion under Weak Supervision

Stutz, D., Geiger, A.

Arxiv, May 2018 (article)

Abstract
We address the problem of 3D shape completion from sparse and noisy point clouds, a fundamental problem in computer vision and robotics. Recent approaches are either data-driven or learning-based: Data-driven approaches rely on a shape model whose parameters are optimized to fit the observations; Learning-based approaches, in contrast, avoid the expensive optimization step by learning to directly predict complete shapes from incomplete observations in a fully-supervised setting. However, full supervision is often not available in practice. In this work, we propose a weakly-supervised learning-based approach to 3D shape completion which neither requires slow optimization nor direct supervision. While we also learn a shape prior on synthetic data, we amortize, i.e., learn, maximum likelihood fitting using deep neural networks resulting in efficient shape completion without sacrificing accuracy. On synthetic benchmarks based on ShapeNet and ModelNet as well as on real robotics data from KITTI and Kinect, we demonstrate that the proposed amortized maximum likelihood approach is able to compete with fully supervised baselines and outperforms data-driven approaches, while requiring less supervision and being significantly faster.

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PDF Project Page Project Page [BibTex]


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Distributed Event-Based State Estimation for Networked Systems: An LMI Approach

Muehlebach, M., Trimpe, S.

IEEE Transactions on Automatic Control, 63(1):269-276, January 2018 (article)

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arXiv (extended version) DOI Project Page [BibTex]

arXiv (extended version) DOI Project Page [BibTex]


{Direct observation of Zhang-Li torque expansion of magnetic droplet solitons}
Direct observation of Zhang-Li torque expansion of magnetic droplet solitons

Chung, S., Tuan Le, Q., Ahlberg, M., Awad, A. A., Weigand, M., Bykova, I., Khymyn, R., Dvornik, M., Mazraati, H., Houshang, A., Jiang, S., Nguyen, T. N. A., Goering, E., Schütz, G., Gräfe, J., \AAkerman, J.

{Physical Review Letters}, 120(21), American Physical Society, Woodbury, N.Y., 2018 (article)

Abstract
Magnetic droplets are nontopological dynamical solitons that can be nucleated in nanocontact based spin torque nano-oscillators (STNOs) with perpendicular magnetic anisotropy free layers. While theory predicts that the droplet should be of the same size as the nanocontact, its inherent drift instability has thwarted attempts at observing it directly using microscopy techniques. Here, we demonstrate highly stable magnetic droplets in all-perpendicular STNOs and present the first detailed droplet images using scanning transmission X-ray microscopy. In contrast to theoretical predictions, we find that the droplet diameter is about twice as large as the nanocontact. By extending the original droplet theory to properly account for the lateral current spread underneath the nanocontact, we show that the large discrepancy primarily arises from current-in-plane Zhang-Li torque adding an outward pressure on the droplet perimeter. Electrical measurements on droplets nucleated using a reversed current in the antiparallel state corroborate this picture.

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DOI [BibTex]

DOI [BibTex]


{Transmission x-ray microscopy at low temperatures: Irregular supercurrent flow at small length scales}
Transmission x-ray microscopy at low temperatures: Irregular supercurrent flow at small length scales

Simmendinger, J., Ruoss, S., Stahl, C., Weigand, M., Gräfe, J., Schütz, G., Albrecht, J.

{Physical Review B}, 97(13), American Physical Society, Woodbury, NY, 2018 (article)

Abstract
Scanning transmission x-ray microscopy has been used to image electric currents in superconducting films at temperatures down to 20 K. We detect significant deviations from a regular current path driven by macroscopic geometrical constraints. The magnetic stray field of supercurrents in a thin YBaCuO film is mapped into a soft-magnetic coating of permalloy. The so-created local magnetization of the ferromagnetic film can be detected by dichroic absorption of polarized x rays. To enable high-quality measurements in transmission geometry, the whole heterostructure of ferromagnet, superconductor, and single-crystalline substrate has been thinned to an overall thickness of less than 1 µm. With this technique, local supercurrents can be analyzed in a wide range of temperatures and magnetic fields. The less than 100 nm spatial resolution of the magnetic signal together with simultaneously obtained nanostructural data allow the correlation of local supercurrents with the micro- and nanostructure of the superconducting film.

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DOI [BibTex]

DOI [BibTex]


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Active microrheology in corrugated channels

Puertas, A. M., Malgaretti, P., Pagonabarraga, I.

The Journal of Chemical Physics, 149(17), American Institute of Physics, Woodbury, N.Y., 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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First-passage dynamics of linear stochastic interface models: weak-noise theory and influence of boundary conditions

Gross, M.

Journal of Statistical Mechanics: Theory and Experiment, 2018, Institute of Physics Publishing, Bristol, England, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Cu@TiO2 Janus microswimmers with a versatile motion mechanism

Wang, L. L., Popescu, M. N., Stavale, F., Ali, A., Gemming, T., Simmchen, J.

Soft Matter, 14(34):6969-6973, Royal Society of Chemistry, Cambridge, UK, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Probing interface localization-delocalization transitions by colloids

Kondrat, S., Vasilyev, O., Dietrich, S.

Journal of Physics: Condensed Matter, 30(41), IOP Publishing, Bristol, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Medical imaging for the tracking of micromotors

Vilela, D., Coss\’\io, U., Parmar, J., Mart\’\inez-Villacorta, A. M., Gómez-Vallejo, V., Llop, J., Sánchez, S.

ACS Nano, 12(2):1220-1227, American Chemical Society, Washington, DC, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Noncontinuous Super-Diffusive Dynamics of a Light-Activated Nanobottle Motor

Xuan, M., Mestre, R., Gao, C., Zhou, C., He, Q., Sánchez, S.

Angewandte Chemie International Edition, 57(23):6838-6842, Wiley-VCH, Weinheim, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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On the origin of forward-backward multiplicity correlations in pp collisions at ultrarelativistic energies

Bravina, L., Bleibel, J., Zabrodin, E.

Physics Letters B, 787, pages: 146-152, North-Holland, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Autophoretic motion in three dimensions

Lisicki, M., Reigh, S., Lauga, E.

Soft Matter, 14(17):3304-3314, Royal Society of Chemistry, Cambridge, UK, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Order-disorder transitions in lattice gases with annealed reactive constraints

Dudka, M., Bénichou, O., Oshanin, G.

Journal of Statistical Mechanics: Theory and Experiment, 2018, Institute of Physics Publishing, Bristol, England, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Bacterial Biohybrid Microswimmers

Bastos-Arrieta, J., Revilla-Guarinos, A., Uspal, W., Simmchen, J.

Frontiers in Robotics and AI, 5, Frontiers Media, Lausanne, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Fluctuational electrodynamics for nonlinear materials in and out of thermal equilibrium

Soo, H., Krüger, M.

Physical Review B, 97(4), American Physical Society, Woodbury, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Local pressure for confined systems

Malgaretti, P., Bier, M.

Physical Review E, 97(2), American Physical Society, Melville, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


Augmented Reality Meets Computer Vision: Efficient Data Generation for Urban Driving Scenes
Augmented Reality Meets Computer Vision: Efficient Data Generation for Urban Driving Scenes

Alhaija, H., Mustikovela, S., Mescheder, L., Geiger, A., Rother, C.

International Journal of Computer Vision (IJCV), 2018, 2018 (article)

Abstract
The success of deep learning in computer vision is based on the availability of large annotated datasets. To lower the need for hand labeled images, virtually rendered 3D worlds have recently gained popularity. Unfortunately, creating realistic 3D content is challenging on its own and requires significant human effort. In this work, we propose an alternative paradigm which combines real and synthetic data for learning semantic instance segmentation and object detection models. Exploiting the fact that not all aspects of the scene are equally important for this task, we propose to augment real-world imagery with virtual objects of the target category. Capturing real-world images at large scale is easy and cheap, and directly provides real background appearances without the need for creating complex 3D models of the environment. We present an efficient procedure to augment these images with virtual objects. In contrast to modeling complete 3D environments, our data augmentation approach requires only a few user interactions in combination with 3D models of the target object category. Leveraging our approach, we introduce a novel dataset of augmented urban driving scenes with 360 degree images that are used as environment maps to create realistic lighting and reflections on rendered objects. We analyze the significance of realistic object placement by comparing manual placement by humans to automatic methods based on semantic scene analysis. This allows us to create composite images which exhibit both realistic background appearance as well as a large number of complex object arrangements. Through an extensive set of experiments, we conclude the right set of parameters to produce augmented data which can maximally enhance the performance of instance segmentation models. Further, we demonstrate the utility of the proposed approach on training standard deep models for semantic instance segmentation and object detection of cars in outdoor driving scenarios. We test the models trained on our augmented data on the KITTI 2015 dataset, which we have annotated with pixel-accurate ground truth, and on the Cityscapes dataset. Our experiments demonstrate that the models trained on augmented imagery generalize better than those trained on fully synthetic data or models trained on limited amounts of annotated real data.

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pdf Project Page [BibTex]

pdf Project Page [BibTex]


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Assessment methodology of promising porous materials for near ambient temperature hydrogen storage applications

Minuto, F. D., Balderas-Xicohténcatl, R., Policicchio, A., Hirscher, M., Agostino, R. G.

{International Journal of Hydrogen Energy}, 43(31):14550-14556, Elsevier, Amsterdam, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Charge polarization, local electroneutrality breakdown and eddy formation due to electroosmosis in varying-section channels

Chinappi, M., Malgaretti, P.

Soft Matter, 14(45):9083-9087, Royal Society of Chemistry, Cambridge, UK, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Critical Casimir interactions and percolation: The quantitative description of critical fluctuations

Vasilyev, O.

Physical Review E, 98(6), American Physical Society, Melville, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Shear-density coupling for a compressible single-component yield-stress fluid

Gross, M., Varnik, F.

Soft Matter, 14(22):4577-4590, Royal Society of Chemistry, Cambridge, UK, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Shape-dependent guidance of active Janus particles by chemically patterned surfaces

Uspal, W. E., Popescu, M. N., Tasinkevych, M., Dietrich, S.

New Journal of Physics, 20, IOP Publishing, Bristol, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Extrapolation to nonequilibrium from coarse-grained response theory

Basu, U., Helden, L., Krüger, M.

Physical Review Letters, 120(18), American Physical Society, Woodbury, N.Y., 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Directed Flow of Micromotors through Alignment Interactions with Micropatterned Ratchets

Katuri, J., Caballero, D., Voituriez, R., Samitier, J., Sánchez, S.

ACS Nano, 12(7):7282-7291, American Chemical Society, Washington, DC, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Spontaneous symmetry breaking of charge-regulated surfaces

Majee, A., Bier, M., Podgornik, R.

Soft Matter, 14(6):985-991, Royal Society of Chemistry, Cambridge, UK, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Electrostatic interaction between dissimilar colloids at fluid interfaces

Majee, A., Schmetzer, T., Bier, M.

Physical Review E, 97(4), American Physical Society, Melville, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Wetting transition of a cylindrical cavity engraved on a hydrophobic surface

Kim, H., Ha, M. Y., Jang, J.

The Journal of Physical Chemistry C, 122(4):2122-2126, American Chemical Society, Washington, D.C., 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Curvature corrections to the nonlocal interfacial model for short-ranged forces

Romero-Enrique, J.M., Squarcini, Alessio, Parry, A. O., Goldbart, P. M.

Physical Review E, 97(6), American Physical Society, Melville, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Incorporation of Terbium into a Microalga Leads to Magnetotactic Swimmers

Santomauro, G., Singh, A., Park, B. W., Mohammadrahimi, M., Erkoc, P., Goering, E., Schütz, G., Sitti, M., Bill, J.

Advanced Biosystems, 2(12):1800039, 2018 (article)

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[BibTex]

[BibTex]


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Thermodynamics, kinetics and selectivity of H2 and D2 on zeolite 5A below 77K

Xiong, R., Balderas-Xicohténcatl, R., Zhang, L., Li, P., Yao, Y., Sang, G., Chen, C., Tang, T., Luo, D., Hirscher, M.

{Microporous and Mesoporous Materials}, 264, pages: 22-27, Elsevier, Amsterdam, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Volumetric hydrogen storage capacity in metal-organic frameworks

Balderas-Xicohténcatl, R., Schlichtenmayer, M., Hirscher, M.

{Energy Technology}, 6(3):578-582, Wiley-VCH, Weinheim, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Effective squirmer models for self-phoretic chemically active spherical colloids

Popescu, M. N., Uspal, W. E., Eskandari, Z., Tasinkevych, M., Dietrich, S.

The European Physical Journal E, 41(12), EDP Sciences; Società Italiana di Fisica; Springer, Les Ulis; Bologna; Heidelberg, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Two time scales for self and collective diffusion near the critical point in a simple patchy model for proteins with floating bonds

Bleibel, J., Habiger, M., Lütje, M., Hirschmann, F., Roosen-Runge, F., Seydel, T., Zhang, F., Schreiber, F., Oettel, M.

Soft Matter, 14(39):8006-8016, Royal Society of Chemistry, Cambridge, UK, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Globulelike Conformation and Enhanced Diffusion of Active Polymers

Bianco, V., Locatelli, E., Malgaretti, P.

Physical Review Letters, 121(21), American Physical Society, Woodbury, N.Y., 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Rheological behavior of colloidal suspension with long-range interactions

Arietaleaniz, S., Malgaretti, P., Pagonabarraga, I., Hidalgo, R. C.

Physical Review E, 98(4), American Physical Society, Melville, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Solvent coarsening around colloids driven by temperature gradients

Roy, S., Dietrich, S., Maciolek, A.

Physical Review E, 97(4), American Physical Society, Melville, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Cross-stream migration of active particles

Katuri, J., Uspal, W., Simmchen, J., López, A. M., Sanchez, S.

Science Advances, 4(1), AAAS, Washington, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Transient dynamics of electric double-layer capacitors: Exact expressions within the Debye-Falkenhagen approximation

Janssen, M., Bier, M.

Physical Review E, 97(5), American Physical Society, Melville, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Coalescence preference and droplet size inequality during fluid phase segregation

Roy, S.

EPL, 121(3), EDP Science, Les-Ulis, 2018 (article)

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DOI [BibTex]


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Structure of interfaces at phase coexistence. Theory and numerics

Delfino, G., Selke, W., Squarcini, A.

Journal of Statistical Mechanics: Theory and Experiment, 2018, Institute of Physics Publishing, Bristol, England, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Power spectral density of a single Brownian trajectory: what one can and cannot learn from it

Krapf, D., Marinari, E., Metzler, Ralf, Oshanin, Gleb, Xu, Xinran, Squarcini, A.

New Journal of Physics, 20, IOP Publishing, Bristol, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Diffusiophoretically induced interactions between chemically active and inert particles

Reigh, Shang-Yik, Chuphal, P., Thakur, S., Kapral, R.

Soft Matter, 14(29):6043-6057, Royal Society of Chemistry, Cambridge, UK, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Collective behavior of colloids due to critical Casimir interactions

Maciolek, A., Dietrich, S.

Reviews of Modern Physics, 90(4), American Physical Society, Minneapolis, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


Learning 3D Shape Completion under Weak Supervision
Learning 3D Shape Completion under Weak Supervision

Stutz, D., Geiger, A.

International Journal of Computer Vision (IJCV), 2018, 2018 (article)

Abstract
We address the problem of 3D shape completion from sparse and noisy point clouds, a fundamental problem in computer vision and robotics. Recent approaches are either data-driven or learning-based: Data-driven approaches rely on a shape model whose parameters are optimized to fit the observations; Learning-based approaches, in contrast, avoid the expensive optimization step by learning to directly predict complete shapes from incomplete observations in a fully-supervised setting. However, full supervision is often not available in practice. In this work, we propose a weakly-supervised learning-based approach to 3D shape completion which neither requires slow optimization nor direct supervision. While we also learn a shape prior on synthetic data, we amortize, i.e., learn, maximum likelihood fitting using deep neural networks resulting in efficient shape completion without sacrificing accuracy. On synthetic benchmarks based on ShapeNet and ModelNet as well as on real robotics data from KITTI and Kinect, we demonstrate that the proposed amortized maximum likelihood approach is able to compete with a fully supervised baseline and outperforms the data-driven approach of Engelmann et al., while requiring less supervision and being significantly faster.

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pdf Project Page [BibTex]

pdf Project Page [BibTex]


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3D nanoprinted plastic kinoform x-ray optics

Sanli, U. T., Ceylan, H., Bykova, I., Weigand, M., Sitti, M., Schütz, G., Keskinbora, K.

{Advanced Materials}, 30(36), Wiley-VCH, Weinheim, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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High volumetric hydrogen storage capacity using interpenetrated metal-organic frameworks

Balderas-Xicohténcatl, R., Schmieder, P., Denysenko, D., Volkmer, D., Hirscher, M.

{Energy Technology}, 6(3):510-512, Wiley-VCH, Weinheim, 2018 (article)

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DOI [BibTex]

DOI [BibTex]