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2018


Softness, Warmth, and Responsiveness Improve Robot Hugs
Softness, Warmth, and Responsiveness Improve Robot Hugs

Block, A. E., Kuchenbecker, K. J.

International Journal of Social Robotics, 11(1):49-64, October 2018 (article)

Abstract
Hugs are one of the first forms of contact and affection humans experience. Due to their prevalence and health benefits, roboticists are naturally interested in having robots one day hug humans as seamlessly as humans hug other humans. This project's purpose is to evaluate human responses to different robot physical characteristics and hugging behaviors. Specifically, we aim to test the hypothesis that a soft, warm, touch-sensitive PR2 humanoid robot can provide humans with satisfying hugs by matching both their hugging pressure and their hugging duration. Thirty relatively young and rather technical participants experienced and evaluated twelve hugs with the robot, divided into three randomly ordered trials that focused on physical robot characteristics (single factor, three levels) and nine randomly ordered trials with low, medium, and high hug pressure and duration (two factors, three levels each). Analysis of the results showed that people significantly prefer soft, warm hugs over hard, cold hugs. Furthermore, users prefer hugs that physically squeeze them and release immediately when they are ready for the hug to end. Taking part in the experiment also significantly increased positive user opinions of robots and robot use.

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link (url) DOI Project Page [BibTex]

2018


link (url) DOI Project Page [BibTex]


Phase separation around a heated colloid in bulk and under confinement
Phase separation around a heated colloid in bulk and under confinement

Roy, S., Maciolek, A.

Soft Matter, 14(46):9326-9335, Royal Society of Chemistry, Cambridge, UK, September 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Task-Driven PCA-Based Design Optimization of Wearable Cutaneous Devices

Pacchierotti, C., Young, E. M., Kuchenbecker, K. J.

IEEE Robotics and Automation Letters, 3(3):2214-2221, July 2018, Presented at ICRA 2018 (article)

Abstract
Small size and low weight are critical requirements for wearable and portable haptic interfaces, making it essential to work toward the optimization of their sensing and actuation systems. This paper presents a new approach for task-driven design optimization of fingertip cutaneous haptic devices. Given one (or more) target tactile interactions to render and a cutaneous device to optimize, we evaluate the minimum number and best configuration of the device’s actuators to minimize the estimated haptic rendering error. First, we calculate the motion needed for the original cutaneous device to render the considered target interaction. Then, we run a principal component analysis (PCA) to search for possible couplings between the original motor inputs, looking also for the best way to reconfigure them. If some couplings exist, we can re-design our cutaneous device with fewer motors, optimally configured to render the target tactile sensation. The proposed approach is quite general and can be applied to different tactile sensors and cutaneous devices. We validated it using a BioTac tactile sensor and custom plate-based 3-DoF and 6-DoF fingertip cutaneous devices, considering six representative target tactile interactions. The algorithm was able to find couplings between each device’s motor inputs, proving it to be a viable approach to optimize the design of wearable and portable cutaneous devices. Finally, we present two examples of optimized designs for our 3-DoF fingertip cutaneous device.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


Robust Physics-based Motion Retargeting with Realistic Body Shapes
Robust Physics-based Motion Retargeting with Realistic Body Shapes

Borno, M. A., Righetti, L., Black, M. J., Delp, S. L., Fiume, E., Romero, J.

Computer Graphics Forum, 37, pages: 6:1-12, July 2018 (article)

Abstract
Motion capture is often retargeted to new, and sometimes drastically different, characters. When the characters take on realistic human shapes, however, we become more sensitive to the motion looking right. This means adapting it to be consistent with the physical constraints imposed by different body shapes. We show how to take realistic 3D human shapes, approximate them using a simplified representation, and animate them so that they move realistically using physically-based retargeting. We develop a novel spacetime optimization approach that learns and robustly adapts physical controllers to new bodies and constraints. The approach automatically adapts the motion of the mocap subject to the body shape of a target subject. This motion respects the physical properties of the new body and every body shape results in a different and appropriate movement. This makes it easy to create a varied set of motions from a single mocap sequence by simply varying the characters. In an interactive environment, successful retargeting requires adapting the motion to unexpected external forces. We achieve robustness to such forces using a novel LQR-tree formulation. We show that the simulated motions look appropriate to each character’s anatomy and their actions are robust to perturbations.

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pdf video Project Page Project Page [BibTex]

pdf video Project Page Project Page [BibTex]


Teaching a Robot Bimanual Hand-Clapping Games via Wrist-Worn {IMU}s
Teaching a Robot Bimanual Hand-Clapping Games via Wrist-Worn IMUs

Fitter, N. T., Kuchenbecker, K. J.

Frontiers in Robotics and Artificial Intelligence, 5(85), July 2018 (article)

Abstract
Colleagues often shake hands in greeting, friends connect through high fives, and children around the world rejoice in hand-clapping games. As robots become more common in everyday human life, they will have the opportunity to join in these social-physical interactions, but few current robots are intended to touch people in friendly ways. This article describes how we enabled a Baxter Research Robot to both teach and learn bimanual hand-clapping games with a human partner. Our system monitors the user's motions via a pair of inertial measurement units (IMUs) worn on the wrists. We recorded a labeled library of 10 common hand-clapping movements from 10 participants; this dataset was used to train an SVM classifier to automatically identify hand-clapping motions from previously unseen participants with a test-set classification accuracy of 97.0%. Baxter uses these sensors and this classifier to quickly identify the motions of its human gameplay partner, so that it can join in hand-clapping games. This system was evaluated by N = 24 naïve users in an experiment that involved learning sequences of eight motions from Baxter, teaching Baxter eight-motion game patterns, and completing a free interaction period. The motion classification accuracy in this less structured setting was 85.9%, primarily due to unexpected variations in motion timing. The quantitative task performance results and qualitative participant survey responses showed that learning games from Baxter was significantly easier than teaching games to Baxter, and that the teaching role caused users to consider more teamwork aspects of the gameplay. Over the course of the experiment, people felt more understood by Baxter and became more willing to follow the example of the robot. Users felt uniformly safe interacting with Baxter, and they expressed positive opinions of Baxter and reported fun interacting with the robot. Taken together, the results indicate that this robot achieved credible social-physical interaction with humans and that its ability to both lead and follow systematically changed the human partner's experience.

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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.

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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Solvent coarsening around colloids driven by temperature gradients

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

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

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DOI [BibTex]

DOI [BibTex]


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Automatically Rating Trainee Skill at a Pediatric Laparoscopic Suturing Task

Oquendo, Y. A., Riddle, E. W., Hiller, D., Blinman, T. A., Kuchenbecker, K. J.

Surgical Endoscopy, 32(4):1840-1857, April 2018 (article)

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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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Immersive Low-Cost Virtual Reality Treatment for Phantom Limb Pain: Evidence from Two Cases

Ambron, E., Miller, A., Kuchenbecker, K. J., Buxbaum, L. J., Coslett, H. B.

Frontiers in Neurology, 9(67):1-7, 2018 (article)

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DOI Project Page [BibTex]

DOI Project Page [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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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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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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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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Heat radiation and transfer in confinement

Asheichyk, K., Krüger, M.

Physical Review B, 98(19), American Physical Society, Woodbury, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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A ferronematic slab in external magnetic fields

Zarubin, G., Bier, M., Dietrich, S.

Soft Matter, 14(48):9806-9818, Royal Society of Chemistry, Cambridge, UK, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Surface-induced nonequilibrium dynamics and critical Casimir forces for model B in film geometry

Gross, M., Gambassi, A., Dietrich, S.

Physical Review E, 98(3), American Physical Society, Melville, NY, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Electrolyte solutions at heterogeneously charged substrates

Mu\ssotter, M., Bier, M., Dietrich, S.

Soft Matter, 14(20):4126-4140, Royal Society of Chemistry, Cambridge, UK, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Vapor nucleation paths in lyophobic nanopores

Tinti, A., Giacomello, A., Casciola, C. M.

European Physical Journal E, 41(4), Springer, Berlin, 2018 (article)

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DOI [BibTex]

DOI [BibTex]


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Fuel-Free Nanocap-Like Motors Actuated Under Visible Light

Wang, Xu, Sridhar, Varun, Guo, Surong, Talebi, Nahid, Miguel-Lopez, Albert, Hahn, Kersten, van Aken, Peter A., Sánchez, Samuel

Advanced Functional Materials, 28(25), Wiley-VCH Verlag GmbH, Weinheim, 2018 (article)

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DOI [BibTex]

DOI [BibTex]