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2020


AirCapRL: Autonomous Aerial Human Motion Capture Using Deep Reinforcement Learning
AirCapRL: Autonomous Aerial Human Motion Capture Using Deep Reinforcement Learning

Tallamraju, R., Saini, N., Bonetto, E., Pabst, M., Liu, Y. T., Black, M., Ahmad, A.

IEEE Robotics and Automation Letters, IEEE Robotics and Automation Letters, 5(4):6678 - 6685, IEEE, October 2020, Also accepted and presented in the 2020 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS). (article)

Abstract
In this letter, we introduce a deep reinforcement learning (DRL) based multi-robot formation controller for the task of autonomous aerial human motion capture (MoCap). We focus on vision-based MoCap, where the objective is to estimate the trajectory of body pose, and shape of a single moving person using multiple micro aerial vehicles. State-of-the-art solutions to this problem are based on classical control methods, which depend on hand-crafted system, and observation models. Such models are difficult to derive, and generalize across different systems. Moreover, the non-linearities, and non-convexities of these models lead to sub-optimal controls. In our work, we formulate this problem as a sequential decision making task to achieve the vision-based motion capture objectives, and solve it using a deep neural network-based RL method. We leverage proximal policy optimization (PPO) to train a stochastic decentralized control policy for formation control. The neural network is trained in a parallelized setup in synthetic environments. We performed extensive simulation experiments to validate our approach. Finally, real-robot experiments demonstrate that our policies generalize to real world conditions.

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link (url) DOI [BibTex]

2020


link (url) DOI [BibTex]


Transient coarsening and the motility of optically heated Janus colloids in a binary liquid mixture
Transient coarsening and the motility of optically heated Janus colloids in a binary liquid mixture

Gomez-Solano, J., Roy, S., Araki, T., Dietrich, S., Maciolek, A.

Soft Matter, 16, pages: 8359-8371, Royal Society of Chemistry, August 2020 (article)

Abstract
A gold-capped Janus particle suspended in a near-critical binary liquid mixture can self-propel under illumination. We have immobilized such a particle in a narrow channel and carried out a combined experimental and theoretical study of the non-equilibrium dynamics of a binary solvent around it – lasting from the very moment of switching illumination on until the steady state is reached. In the theoretical study we use both a purely diffusive and a hydrodynamic model, which we solve numerically. Our results demonstrate a remarkable complexity of the time evolution of the concentration field around the colloid. This evolution is governed by the combined effects of the temperature gradient and the wettability, and crucially depends on whether the colloid is free to move or is trapped. For the trapped colloid, all approaches indicate that the early time dynamics is purely diffusive and characterized by composition layers travelling with constant speed from the surface of the colloid into the bulk of the solvent. Subsequently, hydrodynamic effects set in. Anomalously large nonequilibrium fluctuations, which result from the temperature gradient and the vicinity of the critical point of the binary liquid mixture, give rise to strong concentration fluctuations in the solvent and to permanently changing coarsening patterns not observed for a mobile particle. The early time dynamics around initially still Janus colloids produces a force which is able to set the Janus colloid into motion. The propulsion due to this transient dynamics is in the direction opposite to that observed after the steady state is attained.

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


3D Morphable Face Models - Past, Present and Future
3D Morphable Face Models - Past, Present and Future

Egger, B., Smith, W. A. P., Tewari, A., Wuhrer, S., Zollhoefer, M., Beeler, T., Bernard, F., Bolkart, T., Kortylewski, A., Romdhani, S., Theobalt, C., Blanz, V., Vetter, T.

ACM Transactions on Graphics, 39(5), August 2020 (article)

Abstract
In this paper, we provide a detailed survey of 3D Morphable Face Models over the 20 years since they were first proposed. The challenges in building and applying these models, namely capture, modeling, image formation, and image analysis, are still active research topics, and we review the state-of-the-art in each of these areas. We also look ahead, identifying unsolved challenges, proposing directions for future research and highlighting the broad range of current and future applications.

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project page pdf preprint DOI [BibTex]

project page pdf preprint DOI [BibTex]


Analysis of motor development within the first year of life: 3-{D} motion tracking without markers for early detection of developmental disorders
Analysis of motor development within the first year of life: 3-D motion tracking without markers for early detection of developmental disorders

Parisi, C., Hesse, N., Tacke, U., Rocamora, S. P., Blaschek, A., Hadders-Algra, M., Black, M. J., Heinen, F., Müller-Felber, W., Schroeder, A. S.

Bundesgesundheitsblatt - Gesundheitsforschung - Gesundheitsschutz, 63, pages: 881–890, July 2020 (article)

Abstract
Children with motor development disorders benefit greatly from early interventions. An early diagnosis in pediatric preventive care (U2–U5) can be improved by automated screening. Current approaches to automated motion analysis, however, are expensive, require lots of technical support, and cannot be used in broad clinical application. Here we present an inexpensive, marker-free video analysis tool (KineMAT) for infants, which digitizes 3‑D movements of the entire body over time allowing automated analysis in the future. Three-minute video sequences of spontaneously moving infants were recorded with a commercially available depth-imaging camera and aligned with a virtual infant body model (SMIL model). The virtual image generated allows any measurements to be carried out in 3‑D with high precision. We demonstrate seven infants with different diagnoses. A selection of possible movement parameters was quantified and aligned with diagnosis-specific movement characteristics. KineMAT and the SMIL model allow reliable, three-dimensional measurements of spontaneous activity in infants with a very low error rate. Based on machine-learning algorithms, KineMAT can be trained to automatically recognize pathological spontaneous motor skills. It is inexpensive and easy to use and can be developed into a screening tool for preventive care for children.

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pdf on-line w/ sup mat DOI [BibTex]

pdf on-line w/ sup mat DOI [BibTex]


Learning and Tracking the {3D} Body Shape of Freely Moving Infants from {RGB-D} sequences
Learning and Tracking the 3D Body Shape of Freely Moving Infants from RGB-D sequences

Hesse, N., Pujades, S., Black, M., Arens, M., Hofmann, U., Schroeder, S.

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 42(10):2540-2551, 2020 (article)

Abstract
Statistical models of the human body surface are generally learned from thousands of high-quality 3D scans in predefined poses to cover the wide variety of human body shapes and articulations. Acquisition of such data requires expensive equipment, calibration procedures, and is limited to cooperative subjects who can understand and follow instructions, such as adults. We present a method for learning a statistical 3D Skinned Multi-Infant Linear body model (SMIL) from incomplete, low-quality RGB-D sequences of freely moving infants. Quantitative experiments show that SMIL faithfully represents the RGB-D data and properly factorizes the shape and pose of the infants. To demonstrate the applicability of SMIL, we fit the model to RGB-D sequences of freely moving infants and show, with a case study, that our method captures enough motion detail for General Movements Assessment (GMA), a method used in clinical practice for early detection of neurodevelopmental disorders in infants. SMIL provides a new tool for analyzing infant shape and movement and is a step towards an automated system for GMA.

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pdf Journal DOI [BibTex]

pdf Journal DOI [BibTex]


Interface-mediated spontaneous symmetry breaking and mutual communication between drops containing chemically active particles
Interface-mediated spontaneous symmetry breaking and mutual communication between drops containing chemically active particles

Singh, D., Domínguez, A., Choudhury, U., Kottapalli, S., Popescu, M., Dietrich, S., Fischer, P.

Nature Communications, 11(2210), May 2020 (article)

Abstract
Symmetry breaking and the emergence of self-organized patterns is the hallmark of com- plexity. Here, we demonstrate that a sessile drop, containing titania powder particles with negligible self-propulsion, exhibits a transition to collective motion leading to self-organized flow patterns. This phenomenology emerges through a novel mechanism involving the interplay between the chemical activity of the photocatalytic particles, which induces Mar- angoni stresses at the liquid–liquid interface, and the geometrical confinement provided by the drop. The response of the interface to the chemical activity of the particles is the source of a significantly amplified hydrodynamic flow within the drop, which moves the particles. Furthermore, in ensembles of such active drops long-ranged ordering of the flow patterns within the drops is observed. We show that the ordering is dictated by a chemical com- munication between drops, i.e., an alignment of the flow patterns is induced by the gradients of the chemicals emanating from the active particles, rather than by hydrodynamic interactions.

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link (url) DOI [BibTex]


General Movement Assessment from videos of computed {3D} infant body models is equally effective compared to conventional {RGB} Video rating
General Movement Assessment from videos of computed 3D infant body models is equally effective compared to conventional RGB Video rating

Schroeder, S., Hesse, N., Weinberger, R., Tacke, U., Gerstl, L., Hilgendorff, A., Heinen, F., Arens, M., Bodensteiner, C., Dijkstra, L. J., Pujades, S., Black, M., Hadders-Algra, M.

Early Human Development, 144, May 2020 (article)

Abstract
Background: General Movement Assessment (GMA) is a powerful tool to predict Cerebral Palsy (CP). Yet, GMA requires substantial training hampering its implementation in clinical routine. This inspired a world-wide quest for automated GMA. Aim: To test whether a low-cost, marker-less system for three-dimensional motion capture from RGB depth sequences using a whole body infant model may serve as the basis for automated GMA. Study design: Clinical case study at an academic neurodevelopmental outpatient clinic. Subjects: Twenty-nine high-risk infants were recruited and assessed at their clinical follow-up at 2-4 month corrected age (CA). Their neurodevelopmental outcome was assessed regularly up to 12-31 months CA. Outcome measures: GMA according to Hadders-Algra by a masked GMA-expert of conventional and computed 3D body model (“SMIL motion”) videos of the same GMs. Agreement between both GMAs was assessed, and sensitivity and specificity of both methods to predict CP at ≥12 months CA. Results: The agreement of the two GMA ratings was substantial, with κ=0.66 for the classification of definitely abnormal (DA) GMs and an ICC of 0.887 (95% CI 0.762;0.947) for a more detailed GM-scoring. Five children were diagnosed with CP (four bilateral, one unilateral CP). The GMs of the child with unilateral CP were twice rated as mildly abnormal. DA-ratings of both videos predicted bilateral CP well: sensitivity 75% and 100%, specificity 88% and 92% for conventional and SMIL motion videos, respectively. Conclusions: Our computed infant 3D full body model is an attractive starting point for automated GMA in infants at risk of CP.

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DOI [BibTex]

DOI [BibTex]


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Automatic Discovery of Interpretable Planning Strategies

Skirzyński, J., Becker, F., Lieder, F.

Machine Learning Journal, May 2020 (article) Submitted

Abstract
When making decisions, people often overlook critical information or are overly swayed by irrelevant information. A common approach to mitigate these biases is to provide decisionmakers, especially professionals such as medical doctors, with decision aids, such as decision trees and flowcharts. Designing effective decision aids is a difficult problem. We propose that recently developed reinforcement learning methods for discovering clever heuristics for good decision-making can be partially leveraged to assist human experts in this design process. One of the biggest remaining obstacles to leveraging the aforementioned methods for improving human decision-making is that the policies they learn are opaque to people. To solve this problem, we introduce AI-Interpret: a general method for transforming idiosyncratic policies into simple and interpretable descriptions. Our algorithm combines recent advances in imitation learning and program induction with a new clustering method for identifying a large subset of demonstrations that can be accurately described by a simple, high-performing decision rule. We evaluate our new AI-Interpret algorithm and employ it to translate information-acquisition policies discovered through metalevel reinforcement learning. The results of three large behavioral experiments showed that the provision of decision rules as flowcharts significantly improved people’s planning strategies and decisions across three different classes of sequential decision problems. Furthermore, a series of ablation studies confirmed that our AI-Interpret algorithm was critical to the discovery of interpretable decision rules and that it is ready to be applied to other reinforcement learning problems. We conclude that the methods and findings presented in this article are an important step towards leveraging automatic strategy discovery to improve human decision-making.

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Automatic Discovery of Interpretable Planning Strategies The code for our algorithm and the experiments is available Project Page [BibTex]


Learning Multi-Human Optical Flow
Learning Multi-Human Optical Flow

Ranjan, A., Hoffmann, D. T., Tzionas, D., Tang, S., Romero, J., Black, M. J.

International Journal of Computer Vision (IJCV), (128):873-890, April 2020 (article)

Abstract
The optical flow of humans is well known to be useful for the analysis of human action. Recent optical flow methods focus on training deep networks to approach the problem. However, the training data used by them does not cover the domain of human motion. Therefore, we develop a dataset of multi-human optical flow and train optical flow networks on this dataset. We use a 3D model of the human body and motion capture data to synthesize realistic flow fields in both single-and multi-person images. We then train optical flow networks to estimate human flow fields from pairs of images. We demonstrate that our trained networks are more accurate than a wide range of top methods on held-out test data and that they can generalize well to real image sequences. The code, trained models and the dataset are available for research.

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pdf DOI poster link (url) DOI [BibTex]

pdf DOI poster link (url) DOI [BibTex]


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Advancing Rational Analysis to the Algorithmic Level

Lieder, F., Griffiths, T. L.

Behavioral and Brain Sciences, 43, E27, March 2020 (article)

Abstract
The commentaries raised questions about normativity, human rationality, cognitive architectures, cognitive constraints, and the scope or resource rational analysis (RRA). We respond to these questions and clarify that RRA is a methodological advance that extends the scope of rational modeling to understanding cognitive processes, why they differ between people, why they change over time, and how they could be improved.

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Advancing rational analysis to the algorithmic level DOI [BibTex]

Advancing rational analysis to the algorithmic level DOI [BibTex]


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Learning to Overexert Cognitive Control in a Stroop Task

Bustamante, L., Lieder, F., Musslick, S., Shenhav, A., Cohen, J.

Febuary 2020, Laura Bustamante and Falk Lieder contributed equally to this publication. (article) In revision

Abstract
How do people learn when to allocate how much cognitive control to which task? According to the Learned Value of Control (LVOC) model, people learn to predict the value of alternative control allocations from features of a given situation. This suggests that people may generalize the value of control learned in one situation to other situations with shared features, even when the demands for cognitive control are different. This makes the intriguing prediction that what a person learned in one setting could, under some circumstances, cause them to misestimate the need for, and potentially over-exert control in another setting, even if this harms their performance. To test this prediction, we had participants perform a novel variant of the Stroop task in which, on each trial, they could choose to either name the color (more control-demanding) or read the word (more automatic). However only one of these tasks was rewarded, it changed from trial to trial, and could be predicted by one or more of the stimulus features (the color and/or the word). Participants first learned colors that predicted the rewarded task. Then they learned words that predicted the rewarded task. In the third part of the experiment, we tested how these learned feature associations transferred to novel stimuli with some overlapping features. The stimulus-task-reward associations were designed so that for certain combinations of stimuli the transfer of learned feature associations would incorrectly predict that more highly rewarded task would be color naming, which would require the exertion of control, even though the actually rewarded task was word reading and therefore did not require the engagement of control. Our results demonstrated that participants over-exerted control for these stimuli, providing support for the feature-based learning mechanism described by the LVOC model.

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Learning to Overexert Cognitive Control in a Stroop Task DOI [BibTex]

Learning to Overexert Cognitive Control in a Stroop Task DOI [BibTex]


Real Time Trajectory Prediction Using Deep Conditional Generative Models
Real Time Trajectory Prediction Using Deep Conditional Generative Models

Gomez-Gonzalez, S., Prokudin, S., Schölkopf, B., Peters, J.

IEEE Robotics and Automation Letters, 5(2):970-976, IEEE, January 2020 (article)

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arXiv DOI [BibTex]

arXiv DOI [BibTex]


Toward a Formal Theory of Proactivity
Toward a Formal Theory of Proactivity

Lieder, F., Iwama, G.

January 2020 (article) Submitted

Abstract
Beyond merely reacting to their environment and impulses, people have the remarkable capacity to proactively set and pursue their own goals. But the extent to which they leverage this capacity varies widely across people and situations. The goal of this article is to make the mechanisms and variability of proactivity more amenable to rigorous experiments and computational modeling. We proceed in three steps. First, we develop and validate a mathematically precise behavioral measure of proactivity and reactivity that can be applied across a wide range of experimental paradigms. Second, we propose a formal definition of proactivity and reactivity, and develop a computational model of proactivity in the AX Continuous Performance Task (AX-CPT). Third, we develop and test a computational-level theory of meta-control over proactivity in the AX-CPT that identifies three distinct meta-decision-making problems: intention setting, resolving response conflict between intentions and automaticity, and deciding whether to recall context and intentions into working memory. People's response frequencies in the AX-CPT were remarkably well captured by a mixture between the predictions of our models of proactive and reactive control. Empirical data from an experiment varying the incentives and contextual load of an AX-CPT confirmed the predictions of our meta-control model of individual differences in proactivity. Our results suggest that proactivity can be understood in terms of computational models of meta-control. Our model makes additional empirically testable predictions. Future work will extend our models from proactive control in the AX-CPT to proactive goal creation and goal pursuit in the real world.

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Toward a formal theory of proactivity DOI Project Page [BibTex]


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Axisymmetric spheroidal squirmers and self-diffusiophoretic particles

Pöhnl, R., Popescu, M. N., Uspal, W. E.

Journal of Physics: Condensed Matter, 32(16), IOP Publishing, Bristol, 2020 (article)

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DOI [BibTex]

DOI [BibTex]


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Tracer diffusion on a crowded random Manhattan lattice

Mej\’\ia-Monasterio, C., Nechaev, S., Oshanin, G., Vasilyev, O.

New Journal of Physics, 22(3), IOP Publishing, Bristol, 2020 (article)

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DOI [BibTex]

DOI [BibTex]


Resource-Rational Models of Human Goal Pursuit
Resource-Rational Models of Human Goal Pursuit

Prystawski, B., Mohnert, F., Tošić, M., Lieder, F.

2020 (article)

Abstract
Goal-directed behaviour is a deeply important part of human psychology. People constantly set goals for themselves and pursue them in many domains of life. In this paper, we develop computational models that characterize how humans pursue goals in a complex dynamic environment and test how well they describe human behaviour in an experiment. Our models are motivated by the principle of resource rationality and draw upon psychological insights about people's limited attention and planning capacities. We found that human goal pursuit is qualitatively different and substantially less efficient than optimal goal pursuit. Models of goal pursuit based on the principle of resource rationality captured human behavior better than both a model of optimal goal pursuit and heuristics that are not resource-rational. We conclude that human goal pursuit is jointly shaped by its function, the structure of the environment, and cognitive costs and constraints on human planning and attention. Our findings are an important step toward understanding humans goal pursuit, as cognitive limitations play a crucial role in shaping people's goal-directed behaviour.

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Resource-rational models of human goal pursuit DOI [BibTex]


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Wetting transitions on soft substrates

Napiorkowski, M., Schimmele, L., Dietrich, S.

{EPL}, 129(1), EDP Science, Les-Ulis, 2020 (article)

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DOI [BibTex]

DOI [BibTex]


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Blessing and Curse: How a Supercapacitor Large Capacitance Causes its Slow Charging

Lian, C., Janssen, M., Liu, H., van Roij, R.

Physical Review Letters, 124(7), American Physical Society, Woodbury, N.Y., 2020 (article)

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DOI [BibTex]

DOI [BibTex]


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Interplay of quenching temperature and drift in Brownian dynamics

Khalilian, H., Nejad, M. R., Moghaddam, A. G., Rohwer, C. M.

EPL, 128(6), EDP Science, Les-Ulis, 2020 (article)

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DOI [BibTex]

DOI [BibTex]


Occlusion Boundary: A Formal Definition & Its Detection via Deep Exploration of Context
Occlusion Boundary: A Formal Definition & Its Detection via Deep Exploration of Context

Wang, C., Fu, H., Tao, D., Black, M.

IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2020 (article)

Abstract
Occlusion boundaries contain rich perceptual information about the underlying scene structure and provide important cues in many visual perception-related tasks such as object recognition, segmentation, motion estimation, scene understanding, and autonomous navigation. However, there is no formal definition of occlusion boundaries in the literature, and state-of-the-art occlusion boundary detection is still suboptimal. With this in mind, in this paper we propose a formal definition of occlusion boundaries for related studies. Further, based on a novel idea, we develop two concrete approaches with different characteristics to detect occlusion boundaries in video sequences via enhanced exploration of contextual information (e.g., local structural boundary patterns, observations from surrounding regions, and temporal context) with deep models and conditional random fields. Experimental evaluations of our methods on two challenging occlusion boundary benchmarks (CMU and VSB100) demonstrate that our detectors significantly outperform the current state-of-the-art. Finally, we empirically assess the roles of several important components of the proposed detectors to validate the rationale behind these approaches.

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official version DOI [BibTex]

official version DOI [BibTex]


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Fractal-seaweeds type functionalization of graphene

Amsharov, K., Sharapa, D. I., Vasilyev, O. A., Martin, O., Hauke, F., Görling, A., Soni, H., Hirsch, A.

Carbon, 158, pages: 435-448, Elsevier, Amsterdam, 2020 (article)

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DOI [BibTex]

DOI [BibTex]


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Effective pair interaction of patchy particles in critical fluids

Farahmand Bafi, N., Nowakowski, P., Dietrich, S.

The Journal of Chemical Physics, 152(11), American Institute of Physics, Woodbury, N.Y., 2020 (article)

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DOI [BibTex]

DOI [BibTex]


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Cassie-Wenzel transition of a binary liquid mixture on a nanosculptured surface

Singh, S. L., Schimmele, L., Dietrich, S.

Physical Review E, 101(5), American Physical Society, Melville, NY, 2020 (article)

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DOI [BibTex]

DOI [BibTex]


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Energy storage in steady states under cyclic local energy input

Zhang, Y., Holyst, R., Maciolek, A.

Physical Review E, 101(1), American Physical Society, Melville, NY, 2020 (article)

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DOI [BibTex]

DOI [BibTex]


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Numerical simulations of self-diffusiophoretic colloids at fluid interfaces

Peter, T., Malgaretti, P., Rivas, N., Scagliarini, A., Harting, J., Dietrich, S.

Soft Matter, 16(14):3536-3547, Royal Society of Chemistry, Cambridge, UK, 2020 (article)

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DOI [BibTex]

DOI [BibTex]

2009


Fields of Experts
Fields of Experts

Roth, S., Black, M. J.

International Journal of Computer Vision (IJCV), 82(2):205-29, April 2009 (article)

Abstract
We develop a framework for learning generic, expressive image priors that capture the statistics of natural scenes and can be used for a variety of machine vision tasks. The approach provides a practical method for learning high-order Markov random field (MRF) models with potential functions that extend over large pixel neighborhoods. These clique potentials are modeled using the Product-of-Experts framework that uses non-linear functions of many linear filter responses. In contrast to previous MRF approaches all parameters, including the linear filters themselves, are learned from training data. We demonstrate the capabilities of this Field-of-Experts model with two example applications, image denoising and image inpainting, which are implemented using a simple, approximate inference scheme. While the model is trained on a generic image database and is not tuned toward a specific application, we obtain results that compete with specialized techniques.

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pdf pdf from publisher [BibTex]

2009


pdf pdf from publisher [BibTex]


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Interplay of complete wetting, critical adsorption, and capillary condensation

Drzewinski, A., Maciolek, A., Barasinski, A., Dietrich, S.

Physical Review E, 79, 2009 (article)

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DOI [BibTex]

DOI [BibTex]


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The critical Casimir effect: universal fluctuation-induced forces at work

Gambassi, A., Hertlein, C., Helden, L., Dietrich, S., Bechinger, C.

Europhysics News, 40(01):18-22, 2009 (article)

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DOI [BibTex]

DOI [BibTex]


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Effective interactions of colloids on nematic films

Oettel, M., Dominguez, A., Tasinkevych, M., Dietrich, S.

European Physical Journal E, 28(02):99-111, 2009 (article)

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DOI [BibTex]

DOI [BibTex]


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Self-diffusion and cooperative diffusion in semidilute polymer solutions as measured by fluorescence correlation spectroscopy

Zettl, U., Hoffmann, S. T., Koberling, F., Krausch, G., Enderlein, J., Harnau, L., Ballauff, M.

Macromolecules, 42, pages: 9537-9547, 2009 (article)

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DOI [BibTex]

DOI [BibTex]


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Free-energy function based on an all-atom model for proteins

Yoshidome, T., Oda, K., Harano, Y., Roth, R., Sugita, Y., Ikeguchi, M., Kinoshita, M.

Proteins: Structure, Function, and Bioinformatics, 77(4):950-961, 2009 (article)

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DOI [BibTex]

DOI [BibTex]


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On scale-free and poly-scale behaviors of random hierarchical networks

Avetisov, V. A., Chertovitch, A. V., Nechaev, S .K., Vasilyev, O. A.

Journal of Statistical Mechanics: Theory and Experiment, July 2009, 2009 (article)

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DOI [BibTex]

DOI [BibTex]


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3D Brownian diffusion of submicron-sized particle clusters

Hoffmann, M., Wagner, C. S., Harnau, L., Wittemann, A.

ACS Nano, 3(10):3326-3334, 2009 (article)

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DOI [BibTex]

DOI [BibTex]


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Normal and lateral critical Casimir forces between colloids and patterned substrates

Tröndle, M., Kondrat, S., Gambassi, A., Harnau, L., Dietrich, S.

EPL, 88, 2009 (article)

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DOI [BibTex]


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Critical wetting transitions in two-dimensional systems subject to long-ranged boundary fields

Drzewinski, A., Maciolek, A., Barasinski, A., Dietrich, S.

Physical Review E, 79, 2009 (article)

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DOI [BibTex]


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Derivation of a non-local interfacial model for 3D wetting in an external field

Bernardino, N. R., Parry, A. O., Rascon, C., Romero-Enrique, J. M.

Journal of Physics: Condensed Matter, 21(46), 2009 (article)

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DOI [BibTex]

DOI [BibTex]


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Coupling of rotational motion with shape fluctuations of core-shell microgels having tunable softness

Bolisetty, S., Hoffmann, M., Lekkala, S., Hellweg, T., Ballauff, M., Harnau, L.

Macromolecules, 42, pages: 1264-1269, 2009 (article)

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DOI [BibTex]

DOI [BibTex]


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Strong-disorder paramagnetic-ferromagnetic fixed point in the square-lattice +/-J Ising model

Parisen Toldin, F., Pelissetto, A., Vicari, E.

Journal of Statistical Physics, 135(5):1039-1061, 2009 (article)

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DOI [BibTex]

DOI [BibTex]


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Structure and interaction of flexible dendrimers in concentrated solution

Rosenfeldt, S., Ballauff, M., Lindner, P., Harnau, L.

The Journal of Chemical Physics, 130, 2009 (article)

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DOI [BibTex]

DOI [BibTex]


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Layering of (BMIM)+-based ionic liquids at a charged sapphire interface

Mezger, M., Schramm, S., Schröder, H., Reichert, H., Deutsch, M., de Souza, E. J., Okasinski, J. S., Ocko, B. M., Honkimäki, V., Dosch, H.

Journal of Chemical Physics, 131, 2009 (article)

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DOI [BibTex]

DOI [BibTex]


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Nano-droplets on structured substrates

Rauscher, M. A., Dietrich, S.

Soft Matter, 5(16):2997-3001, 2009 (article)

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DOI [BibTex]

DOI [BibTex]


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Self-assembly of Janus cylinders into hierarchical superstructures

Walther, A., Drechsler, M., Rosenfeldt, S., Harnau, L., Ballauff, M., Abetz, V., Müller, A. H. E.

Journal of the American Chemical Society, 131, pages: 4720-4728, 2009 (article)

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DOI [BibTex]

DOI [BibTex]


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Solvent-mediated interactions between nanoparticles at fluid interfaces

Bresme, F., Lehle, H., Oettel, M.

Journal of Chemical Physics, 130(21), 2009 (article)

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DOI [BibTex]

DOI [BibTex]


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Diffusion of a sphere in a dilute solution of polymer coils

Krüger, M., Rauscher, M.

Journal of Chemical Physics, 131(9), 2009 (article)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Dynamics of nanodroplets on topographically structured substrates

Moosavi, A., Rauscher, M., Dietrich, S.

Journal of Physics: Condensed Matter, 21(46), 2009 (article)

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DOI [BibTex]

DOI [BibTex]


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Critical Casimir effect in classical binary liquid mixtures

Gambassi, A., Maciolek, A., Hertlein, C., Nellen, U., Helden, L., Bechinger, C., Dietrich, S.

Physical Review E, 80, 2009 (article)

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DOI [BibTex]

DOI [BibTex]


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Phase transitions and ordering of confined dipolar fluids

Szalai, I., Dietrich, S.

European Physical Journal E, 28(3):347-359, 2009 (article)

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DOI [BibTex]

DOI [BibTex]


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Nonlinear dielectric effect of dipolar fluids

Szalai, I., Nagy, S., Dietrich, S.

Journal of Chemical Physics, 131(15), 2009 (article)

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DOI [BibTex]

DOI [BibTex]


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Some physical applications of random hierarchical matrices

Avetisov, V. A., Bikulov, A. K., Vasilyev, O. A., Nechaev, S. K., Chertovich, A. V.

Journal of Experimental and Theoretical Physics, 109(3):485-504, 2009 (article)

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DOI [BibTex]

DOI [BibTex]