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2018


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Learning-based solution to phase error correction in T2*-weighted GRE scans

Loktyushin, A., Ehses, P., Schölkopf, B., Scheffler, K.

1st International conference on Medical Imaging with Deep Learning (MIDL), July 2018 (conference)

ei

link (url) [BibTex]

2018


link (url) [BibTex]


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The Mirage of Action-Dependent Baselines in Reinforcement Learning

Tucker, G., Bhupatiraju, S., Gu, S., Turner, R., Ghahramani, Z., Levine, S.

Proceedings of the 35th International Conference on Machine Learning (ICML), 80, pages: 5022-5031, Proceedings of Machine Learning Research, (Editors: Dy, Jennifer and Krause, Andreas), PMLR, July 2018 (conference)

ei

PDF link (url) Project Page [BibTex]

PDF link (url) Project Page [BibTex]


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Intrinsic disentanglement: an invariance view for deep generative models

Besserve, M., Sun, R., Schölkopf, B.

Workshop on Theoretical Foundations and Applications of Deep Generative Models at ICML, July 2018 (conference)

ei

PDF [BibTex]

PDF [BibTex]


Thumb xl 2018 prd
Assessing Generative Models via Precision and Recall

Sajjadi, M. S. M., Bachem, O., Lucic, M., Bousquet, O., Gelly, S.

Workshop on Theoretical Foundations and Applications of Deep Generative Models (TADGM) at the 35th International Conference on Machine Learning (ICML), July 2018 (conference)

ei

arXiv [BibTex]

arXiv [BibTex]


Thumb xl 2018 tgan
Tempered Adversarial Networks

Sajjadi, M. S. M., Parascandolo, G., Mehrjou, A., Schölkopf, B.

Proceedings of the 35th International Conference on Machine Learning (ICML), 80, pages: 4448-4456, Proceedings of Machine Learning Research, (Editors: Dy, Jennifer and Krause, Andreas), PMLR, July 2018 (conference)

ei

arXiv link (url) Project Page [BibTex]

arXiv link (url) Project Page [BibTex]


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PIPPS: Flexible Model-Based Policy Search Robust to the Curse of Chaos

Parmas, P., Rasmussen, C., Peters, J., Doya, K.

Proceedings of the 35th International Conference on Machine Learning (ICML), 80, pages: 4065-4074, Proceedings of Machine Learning Research, (Editors: Dy, Jennifer and Krause, Andreas), PMLR, July 2018 (conference)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Learning Independent Causal Mechanisms

Parascandolo, G., Kilbertus, N., Rojas-Carulla, M., Schölkopf, B.

Proceedings of the 35th International Conference on Machine Learning (ICML), 80, pages: 4033-4041, Proceedings of Machine Learning Research, (Editors: Dy, Jennifer and Krause, Andreas), PMLR, July 2018 (conference)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Nonstationary GANs: Analysis as Nonautonomous Dynamical Systems

Mehrjou, A., Schölkopf, B.

Workshop on Theoretical Foundations and Applications of Deep Generative Models at ICML, July 2018 (conference)

ei

PDF [BibTex]

PDF [BibTex]


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Probabilistic Recurrent State-Space Models

Doerr, A., Daniel, C., Schiegg, M., Nguyen-Tuong, D., Schaal, S., Toussaint, M., Trimpe, S.

In Proceedings of the International Conference on Machine Learning (ICML), International Conference on Machine Learning (ICML), July 2018 (inproceedings)

Abstract
State-space models (SSMs) are a highly expressive model class for learning patterns in time series data and for system identification. Deterministic versions of SSMs (e.g., LSTMs) proved extremely successful in modeling complex time-series data. Fully probabilistic SSMs, however, unfortunately often prove hard to train, even for smaller problems. To overcome this limitation, we propose a scalable initialization and training algorithm based on doubly stochastic variational inference and Gaussian processes. In the variational approximation we propose in contrast to related approaches to fully capture the latent state temporal correlations to allow for robust training.

am ics

arXiv pdf Project Page [BibTex]

arXiv pdf Project Page [BibTex]


Thumb xl octo turned
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.

am

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


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Differentially Private Database Release via Kernel Mean Embeddings

Balog, M., Tolstikhin, I., Schölkopf, B.

Proceedings of the 35th International Conference on Machine Learning (ICML), 80, pages: 423-431, Proceedings of Machine Learning Research, (Editors: Dy, Jennifer and Krause, Andreas), PMLR, July 2018 (conference)

ei

link (url) Project Page Project Page [BibTex]

link (url) Project Page Project Page [BibTex]


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On Matching Pursuit and Coordinate Descent

Locatello, F., Raj, A., Praneeth Karimireddy, S., Rätsch, G., Schölkopf, B., Stich, S. U., Jaggi, M.

Proceedings of the 35th International Conference on Machine Learning (ICML), 80, pages: 3204-3213, Proceedings of Machine Learning Research, (Editors: Dy, Jennifer and Krause, Andreas), PMLR, July 2018 (conference)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Iterative Model-Fitting and Local Controller Optimization - Towards a Better Understanding of Convergence Properties

Wüthrich, M., Schölkopf, B.

Workshop on Prediction and Generative Modeling in Reinforcement Learning at ICML, July 2018 (conference)

ei

PDF link (url) [BibTex]

PDF link (url) [BibTex]


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Counterfactual Mean Embedding: A Kernel Method for Nonparametric Causal Inference

Muandet, K., Kanagawa, M., Saengkyongam, S., Marukata, S.

Workshop on Machine Learning for Causal Inference, Counterfactual Prediction, and Autonomous Action (CausalML) at ICML, July 2018 (conference)

ei

[BibTex]

[BibTex]


Thumb xl cover book high 1
Colloidal Chemical Nanomotors

Alarcon-Correa, M.

Colloidal Chemical Nanomotors, pages: 150, Cuvillier Verlag, MPI-IS , June 2018 (phdthesis)

Abstract
Synthetic sophisticated nanostructures represent a fundamental building block for the development of nanotechnology. The fabrication of nanoparticles complex in structure and material composition is key to build nanomachines that can operate as man-made nanoscale motors, which autonomously convert external energy into motion. To achieve this, asymmetric nanoparticles were fabricated combining a physical vapor deposition technique known as NanoGLAD and wet chemical synthesis. This thesis primarily concerns three complex colloidal systems that have been developed: i)Hollow nanocup inclusion complexes that have a single Au nanoparticle in their pocket. The Au particle can be released with an external trigger. ii)The smallest self-propelling nanocolloids that have been made to date, which give rise to a local concentration gradient that causes enhanced diffusion of the particles. iii)Enzyme-powered pumps that have been assembled using bacteriophages as biological nanoscaffolds. This construct also can be used for enzyme recovery after heterogeneous catalysis.

pf

[BibTex]

[BibTex]


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Infinite Factorial Finite State Machine for Blind Multiuser Channel Estimation

Ruiz, F. J. R., Valera, I., Svensson, L., Perez-Cruz, F.

IEEE Transactions on Cognitive Communications and Networking, 4(2):177-191, June 2018 (article)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


Thumb xl 2017 frvsr
Frame-Recurrent Video Super-Resolution

Sajjadi, M. S. M., Vemulapalli, R., Brown, M.

IEEE Conference on Computer Vision and Pattern Recognition (CVPR) , June 2018 (conference)

ei

ArXiv link (url) [BibTex]

ArXiv link (url) [BibTex]


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Learning Face Deblurring Fast and Wide

Jin, M., Hirsch, M., Favaro, P.

The IEEE Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, pages: 745-753, June 2018 (conference)

ei

link (url) [BibTex]

link (url) [BibTex]


Thumb xl propultion. of helical m
Bioinspired microrobots

Palagi, S., Fischer, P.

Nature Reviews Materials, 3, pages: 113–124, May 2018 (article)

Abstract
Microorganisms can move in complex media, respond to the environment and self-organize. The field of microrobotics strives to achieve these functions in mobile robotic systems of sub-millimetre size. However, miniaturization of traditional robots and their control systems to the microscale is not a viable approach. A promising alternative strategy in developing microrobots is to implement sensing, actuation and control directly in the materials, thereby mimicking biological matter. In this Review, we discuss design principles and materials for the implementation of robotic functionalities in microrobots. We examine different biological locomotion strategies, and we discuss how they can be artificially recreated in magnetic microrobots and how soft materials improve control and performance. We show that smart, stimuli-responsive materials can act as on-board sensors and actuators and that ‘active matter’ enables autonomous motion, navigation and collective behaviours. Finally, we provide a critical outlook for the field of microrobotics and highlight the challenges that need to be overcome to realize sophisticated microrobots, which one day might rival biological machines.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Wasserstein Auto-Encoders

Tolstikhin, I., Bousquet, O., Gelly, S., Schölkopf, B.

6th International Conference on Learning Representations (ICLR), May 2018 (conference)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Fidelity-Weighted Learning

Dehghani, M., Mehrjou, A., Gouws, S., Kamps, J., Schölkopf, B.

6th International Conference on Learning Representations (ICLR), May 2018 (conference)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Inducing Probabilistic Context-Free Grammars for the Sequencing of Movement Primitives

Lioutikov, R., Maeda, G., Veiga, F., Kersting, K., Peters, J.

IEEE International Conference on Robotics and Automation, (ICRA), pages: 1-8, IEEE, May 2018 (conference)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Sobolev GAN

Mroueh, Y., Li*, C., Sercu*, T., Raj*, A., Cheng, Y.

6th International Conference on Learning Representations (ICLR), May 2018, *equal contribution (conference)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Assisting Movement Training and Execution With Visual and Haptic Feedback

Ewerton, M., Rother, D., Weimar, J., Kollegger, G., Wiemeyer, J., Peters, J., Maeda, G.

Frontiers in Neurorobotics, 12, May 2018 (article)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


Thumb xl icra2018
Soft Miniaturized Linear Actuators Wirelessly Powered by Rotating Permanent Magnets

Qiu, T., Palagi, S., Sachs, J., Fischer, P.

In 2018 IEEE International Conference on Robotics and Automation (ICRA), pages: 3595-3600, May 2018 (inproceedings)

Abstract
Wireless actuation by magnetic fields allows for the operation of untethered miniaturized devices, e.g. in biomedical applications. Nevertheless, generating large controlled forces over relatively large distances is challenging. Magnetic torques are easier to generate and control, but they are not always suitable for the tasks at hand. Moreover, strong magnetic fields are required to generate a sufficient torque, which are difficult to achieve with electromagnets. Here, we demonstrate a soft miniaturized actuator that transforms an externally applied magnetic torque into a controlled linear force. We report the design, fabrication and characterization of both the actuator and the magnetic field generator. We show that the magnet assembly, which is based on a set of rotating permanent magnets, can generate strong controlled oscillating fields over a relatively large workspace. The actuator, which is 3D-printed, can lift a load of more than 40 times its weight. Finally, we show that the actuator can be further miniaturized, paving the way towards strong, wirelessly powered microactuators.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Temporal Difference Models: Model-Free Deep RL for Model-Based Control

Pong*, V., Gu*, S., Dalal, M., Levine, S.

6th International Conference on Learning Representations (ICLR), May 2018, *equal contribution (conference)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Wasserstein Auto-Encoders: Latent Dimensionality and Random Encoders

Rubenstein, P. K., Schölkopf, B., Tolstikhin, I.

Workshop at the 6th International Conference on Learning Representations (ICLR), May 2018 (conference)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning

Eysenbach, B., Gu, S., Ibarz, J., Levine, S.

6th International Conference on Learning Representations (ICLR), May 2018 (conference)

ei

Videos link (url) Project Page [BibTex]

Videos link (url) Project Page [BibTex]


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Online Learning of a Memory for Learning Rates

(nominated for best paper award)

Meier, F., Kappler, D., Schaal, S.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2018, IEEE, International Conference on Robotics and Automation, May 2018, accepted (inproceedings)

Abstract
The promise of learning to learn for robotics rests on the hope that by extracting some information about the learning process itself we can speed up subsequent similar learning tasks. Here, we introduce a computationally efficient online meta-learning algorithm that builds and optimizes a memory model of the optimal learning rate landscape from previously observed gradient behaviors. While performing task specific optimization, this memory of learning rates predicts how to scale currently observed gradients. After applying the gradient scaling our meta-learner updates its internal memory based on the observed effect its prediction had. Our meta-learner can be combined with any gradient-based optimizer, learns on the fly and can be transferred to new optimization tasks. In our evaluations we show that our meta-learning algorithm speeds up learning of MNIST classification and a variety of learning control tasks, either in batch or online learning settings.

am

pdf video code [BibTex]

pdf video code [BibTex]


Thumb xl 2018 tgan
Tempered Adversarial Networks

Sajjadi, M. S. M., Parascandolo, G., Mehrjou, A., Schölkopf, B.

Workshop at the 6th International Conference on Learning Representations (ICLR), May 2018 (conference)

ei

arXiv [BibTex]

arXiv [BibTex]


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Learning Coupled Forward-Inverse Models with Combined Prediction Errors

Koert, D., Maeda, G., Neumann, G., Peters, J.

IEEE International Conference on Robotics and Automation, (ICRA), pages: 2433-2439, IEEE, May 2018 (conference)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Learning Disentangled Representations with Wasserstein Auto-Encoders

Rubenstein, P. K., Schölkopf, B., Tolstikhin, I.

Workshop at the 6th International Conference on Learning Representations (ICLR), May 2018 (conference)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Automatic Estimation of Modulation Transfer Functions

Bauer, M., Volchkov, V., Hirsch, M., Schölkopf, B.

IEEE International Conference on Computational Photography (ICCP), May 2018 (conference)

ei sf

DOI [BibTex]

DOI [BibTex]


Thumb xl learning ct w asm block diagram detailed
Learning Sensor Feedback Models from Demonstrations via Phase-Modulated Neural Networks

Sutanto, G., Su, Z., Schaal, S., Meier, F.

In Proceedings of the IEEE International Conference on Robotics and Automation (ICRA) 2018, IEEE, International Conference on Robotics and Automation, May 2018 (inproceedings)

am

pdf video [BibTex]

pdf video [BibTex]


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Causal Discovery Using Proxy Variables

Rojas-Carulla, M., Baroni, M., Lopez-Paz, D.

Workshop at 6th International Conference on Learning Representations (ICLR), May 2018 (conference)

ei

link (url) [BibTex]

link (url) [BibTex]


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Sample and Feedback Efficient Hierarchical Reinforcement Learning from Human Preferences

Pinsler, R., Akrour, R., Osa, T., Peters, J., Neumann, G.

IEEE International Conference on Robotics and Automation, (ICRA), pages: 596-601, IEEE, May 2018 (conference)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


Thumb xl graphene silver hybrid
Graphene-silver hybrid devices for sensitive photodetection in the ultraviolet

Paria, D., Jeong, H. H., Vadakkumbatt, V., Deshpande, P., Fischer, P., Ghosh, A., Ghosh, A.

Nanoscale, 10, pages: 7685-7693, April 2018 (article)

Abstract
The weak light-matter interaction in graphene can be enhanced with a number of strategies, among which sensitization with plasmonic nanostructures is particularly attractive. This has resulted in the development of graphene-plasmonic hybrid systems with strongly enhanced photodetection efficiencies in the visible and the IR, but none in the UV. Here, we describe a silver nanoparticle-graphene stacked optoelectronic device that shows strong enhancement of its photoresponse across the entire UV spectrum. The device fabrication strategy is scalable and modular. Self-assembly techniques are combined with physical shadow growth techniques to fabricate a regular large-area array of 50 nm silver nanoparticles onto which CVD graphene is transferred. The presence of the silver nanoparticles resulted in a plasmonically enhanced photoresponse as high as 3.2 A W-1 in the wavelength range from 330 nm to 450 nm. At lower wavelengths, close to the Van Hove singularity of the density of states in graphene, we measured an even higher responsivity of 14.5 A W-1 at 280 nm, which corresponds to a more than 10 000-fold enhancement over the photoresponse of native graphene.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Nanoparticles on the move for medicine

Fischer, P.

Physics World Focus on Nanotechnology, pages: 26028, (Editors: Margaret Harris), IOP Publishing Ltd and individual contributors, April 2018 (article)

Abstract
Peer Fischer outlines the prospects for creating “nanoswimmers” that can be steered through the body to deliver drugs directly to their targets Molecules don’t move very fast on their own. If they had to rely solely on diffusion – a slow and inefficient process linked to the Brownian motion of small particles and molecules in solution – then a protein mole­cule, for instance, would take around three weeks to travel a single centimetre down a nerve fibre. This is why active transport mechanisms exist in cells and in the human body: without them, all the processes of life would happen at a pace that would make snails look speedy.

pf

link (url) [BibTex]

link (url) [BibTex]


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Group invariance principles for causal generative models

Besserve, M., Shajarisales, N., Schölkopf, B., Janzing, D.

Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), 84, pages: 557-565, Proceedings of Machine Learning Research, (Editors: Amos Storkey and Fernando Perez-Cruz), PMLR, April 2018 (conference)

ei

link (url) [BibTex]

link (url) [BibTex]


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Boosting Variational Inference: an Optimization Perspective

Locatello, F., Khanna, R., Ghosh, J., Rätsch, G.

Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS), 84, pages: 464-472, Proceedings of Machine Learning Research, (Editors: Amos Storkey and Fernando Perez-Cruz), PMLR, April 2018 (conference)

ei

link (url) Project Page Project Page [BibTex]

link (url) Project Page Project Page [BibTex]


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Mixture of Attractors: A Novel Movement Primitive Representation for Learning Motor Skills From Demonstrations

Manschitz, S., Gienger, M., Kober, J., Peters, J.

IEEE Robotics and Automation Letters, 3(2):926-933, April 2018 (article)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Probabilistic movement primitives under unknown system dynamics

Paraschos, A., Rueckert, E., Peters, J., Neumann, G.

Advanced Robotics, 32(6):297-310, April 2018 (article)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Cause-Effect Inference by Comparing Regression Errors

Blöbaum, P., Janzing, D., Washio, T., Shimizu, S., Schölkopf, B.

Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS) , 84, pages: 900-909, Proceedings of Machine Learning Research, (Editors: Amos Storkey and Fernando Perez-Cruz), PMLR, April 2018 (conference)

ei

link (url) [BibTex]

link (url) [BibTex]


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Will People Like Your Image? Learning the Aesthetic Space

Schwarz, K., Wieschollek, P., Lensch, H. P. A.

2018 IEEE Winter Conference on Applications of Computer Vision (WACV), pages: 2048-2057, March 2018 (conference)

ei

DOI [BibTex]

DOI [BibTex]


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An Algorithmic Perspective on Imitation Learning

Osa, T., Pajarinen, J., Neumann, G., Bagnell, J., Abbeel, P., Peters, J.

Foundations and Trends in Robotics, 7(1-2):1-179, March 2018 (article)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Using Probabilistic Movement Primitives in Robotics

Paraschos, A., Daniel, C., Peters, J., Neumann, G.

Autonomous Robots, 42(3):529-551, March 2018 (article)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Representation of sensory uncertainty in macaque visual cortex

Goris, R., Henaff, O., Meding, K.

Computational and Systems Neuroscience (COSYNE) 2018, March 2018 (poster)

ei

[BibTex]

[BibTex]


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A kernel-based approach to learning contact distributions for robot manipulation tasks

Kroemer, O., Leischnig, S., Luettgen, S., Peters, J.

Autonomous Robots, 42(3):581-600, March 2018 (article)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


Thumb xl singh et al 2018 advanced functional materials
Photogravitactic Microswimmers

Singh, D. P., Uspal, W. E., Popescu, M. N., Wilson, L. G., Fischer, P.

Adv. Func. Mat., 28, pages: 1706660, Febuary 2018 (article)

Abstract
Abstract Phototactic microorganisms are commonly observed to respond to natural sunlight by swimming upward against gravity. This study demonstrates that synthetic photochemically active microswimmers can also swim against gravity. The particles initially sediment and, when illuminated at low light intensities exhibit wall‐bound states of motion near the bottom surface. Upon increasing the intensity of light, the artificial swimmers lift off from the wall and swim against gravity and away from the light source. This motion in the bulk has been further confirmed using holographic microscopy. A theoretical model is presented within the framework of self‐diffusiophoresis, which allows to unequivocally identify the photochemical activity and the phototactic response as key mechanisms in the observed phenomenology. Since the lift‐off threshold intensity depends on the particle size, it can be exploited to selectively address particles with the same density from a polydisperse mixture of active particles and move them in or out of the boundary region. This study provides a simple design strategy to fabricate artificial microswimmers whose two‐ or three‐dimensional swimming behavior can be controlled with light.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]


Thumb xl matuschek et al 2018 small
Chiral Plasmonic Hydrogen Sensors

Matuschek, M., Singh, D. P., Hyeon-Ho, J., Nesterov, M., Weiss, T., Fischer, P., Neubrech, F., Na Liu, L.

Small, 14(7):1702990, Febuary 2018 (article)

Abstract
In this article, a chiral plasmonic hydrogen‐sensing platform using palladium‐based nanohelices is demonstrated. Such 3D chiral nanostructures fabricated by nanoglancing angle deposition exhibit strong circular dichroism both experimentally and theoretically. The chiroptical properties of the palladium nanohelices are altered upon hydrogen uptake and sensitively depend on the hydrogen concentration. Such properties are well suited for remote and spark‐free hydrogen sensing in the flammable range. Hysteresis is reduced, when an increasing amount of gold is utilized in the palladium‐gold hybrid helices. As a result, the linearity of the circular dichroism in response to hydrogen is significantly improved. The chiral plasmonic sensor scheme is of potential interest for hydrogen‐sensing applications, where good linearity and high sensitivity are required.

pf

link (url) DOI [BibTex]

link (url) DOI [BibTex]