Header logo is


2016


no image
Probabilistic Inference for Determining Options in Reinforcement Learning

Daniel, C., van Hoof, H., Peters, J., Neumann, G.

Machine Learning, Special Issue, 104(2):337-357, (Editors: Gärtner, T., Nanni, M., Passerini, A. and Robardet, C.), European Conference on Machine Learning im Machine Learning, Journal Track, 2016, Best Student Paper Award of ECML-PKDD 2016 (article)

am ei

DOI Project Page [BibTex]

2016


DOI Project Page [BibTex]


no image
PGO wave-triggered functional MRI: mapping the networks underlying synaptic consolidation

Logothetis, N. K., Murayama, Y., Ramirez-Villegas, J. F., Besserve, M., Evrard, H.

47th Annual Meeting of the Society for Neuroscience (Neuroscience), 2016 (poster)

ei

[BibTex]

[BibTex]


no image
Unsupervised Domain Adaptation in the Wild : Dealing with Asymmetric Label Set

Mittal, A., Raj, A., Namboodiri, V. P., Tuytelaars, T.

2016 (misc)

ei

Arxiv [BibTex]

Arxiv [BibTex]


no image
Influence of initial fixation position in scene viewing

Rothkegel, L. O. M., Trukenbrod, H. A., Schütt, H. H., Wichmann, F. A., Engbert, R.

Vision Research, 129, pages: 33-49, 2016 (article)

ei

link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


no image
Testing models of peripheral encoding using metamerism in an oddity paradigm

Wallis, T. S. A., Bethge, M., Wichmann, F. A.

Journal of Vision, 16(2), 2016 (article)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


no image
Modeling Confounding by Half-Sibling Regression

Schölkopf, B., Hogg, D., Wang, D., Foreman-Mackey, D., Janzing, D., Simon-Gabriel, C. J., Peters, J.

Proceedings of the National Academy of Science, 113(27):7391-7398, 2016 (article)

ei

Code link (url) DOI Project Page [BibTex]

Code link (url) DOI Project Page [BibTex]


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

Klenske, E. D., Hennig, P.

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

ei pn

PDF link (url) [BibTex]

PDF link (url) [BibTex]


no image
A Population Based Gaussian Mixture Model Incorporating 18F-FDG-PET and DW-MRI Quantifies Tumor Tissue Classes

Divine, M. R., Katiyar, P., Kohlhofer, U., Quintanilla-Martinez, L., Disselhorst, J. A., Pichler, B. J.

Journal of Nuclear Medicine, 57(3):473-479, 2016 (article)

ei

DOI [BibTex]

DOI [BibTex]


no image
Nonlinear functional causal models for distinguishing cause from effect

Zhang, K., Hyvärinen, A.

In Statistics and Causality: Methods for Applied Empirical Research, pages: 185-201, 8, 1st, (Editors: Wolfgang Wiedermann and Alexander von Eye), John Wiley & Sons, Inc., 2016 (inbook)

ei

[BibTex]

[BibTex]


Thumb xl nao
Ensuring Ethical Behavior from Autonomous Systems

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

In Artificial Intelligence Applied to Assistive Technologies and Smart Environments, Papers from the 2016 AAAI Workshop, Phoenix, Arizona, USA, February 12, 2016, 2016 (inproceedings)

am

link (url) [BibTex]

link (url) [BibTex]


no image
Painfree and accurate Bayesian estimation of psychometric functions for (potentially) overdispersed data

Schütt, H. H., Harmeling, S., Macke, J. H., Wichmann, F. A.

Vision Research, 122, pages: 105-123, 2016 (article)

ei

link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


no image
A cognitive brain–computer interface for patients with amyotrophic lateral sclerosis

Hohmann, M., Fomina, T., Jayaram, V., Widmann, N., Förster, C., Just, J., Synofzik, M., Schölkopf, B., Schöls, L., Grosse-Wentrup, M.

In Brain-Computer Interfaces: Lab Experiments to Real-World Applications, 228(Supplement C):221-239, 8, Progress in Brain Research, (Editors: Damien Coyle), Elsevier, 2016 (incollection)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


no image
Hierarchical Relative Entropy Policy Search

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

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

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


no image
Kernel Mean Shrinkage Estimators

Muandet, K., Sriperumbudur, B., Fukumizu, K., Gretton, A., Schölkopf, B.

Journal of Machine Learning Research, 17(48):1-41, 2016 (article)

ei

link (url) [BibTex]

link (url) [BibTex]


no image
Learning to Deblur

Schuler, C. J., Hirsch, M., Harmeling, S., Schölkopf, B.

IEEE Transactions on Pattern Analysis and Machine Intelligence, 38(7):1439-1451, IEEE, 2016 (article)

ei

DOI [BibTex]

DOI [BibTex]


no image
Transfer Learning in Brain-Computer Interfaces

Jayaram, V., Alamgir, M., Altun, Y., Schölkopf, B., Grosse-Wentrup, M.

IEEE Computational Intelligence Magazine, 11(1):20-31, 2016 (article)

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


no image
MERLiN: Mixture Effect Recovery in Linear Networks

Weichwald, S., Grosse-Wentrup, M., Gretton, A.

IEEE Journal of Selected Topics in Signal Processing, 10(7):1254-1266, 2016 (article)

ei

Arxiv Code PDF DOI Project Page [BibTex]

Arxiv Code PDF DOI Project Page [BibTex]


no image
Causal inference using invariant prediction: identification and confidence intervals

Peters, J., Bühlmann, P., Meinshausen, N.

Journal of the Royal Statistical Society, Series B (Statistical Methodology), 78(5):947-1012, 2016, (with discussion) (article)

ei

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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

Spirtes, P., Zhang, K.

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

ei

DOI [BibTex]

DOI [BibTex]


no image
Towards Robust Online Inverse Dynamics Learning

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

Proceedings of the IEEE/RSJ Conference on Intelligent Robots and Systems, IEEE, IROS, 2016 (conference) Accepted

am

fmeier_iros_2016 [BibTex]

fmeier_iros_2016 [BibTex]


Thumb xl front small
Self-Supervised Regrasping using Spatio-Temporal Tactile Features and Reinforcement Learning

Chebotar, Y., Hausman, K., Su, Z., Sukhatme, G., Schaal, S.

In International Conference on Intelligent Robots and Systems (IROS) 2016, IEEE/RSJ International Conference on Intelligent Robots and Systems, 2016 (inproceedings)

am

pdf video [BibTex]

pdf video [BibTex]


no image
Self-regulation of brain rhythms in the precuneus: a novel BCI paradigm for patients with ALS

Fomina, T., Lohmann, G., Erb, M., Ethofer, T., Schölkopf, B., Grosse-Wentrup, M.

Journal of Neural Engineering, 13(6):066021, 2016 (article)

ei

link (url) Project Page [BibTex]


Thumb xl toc image patent
Method for encapsulating a nanostructure, coated nanostructure and use of a coated nanostructure

Jeong, H. H., Lee, T. C., Fischer, P.

Google Patents, 2016, WO Patent App. PCT/EP2016/056,377 (patent)

Abstract
The present invention relates to a method for encapsulating a nanostructure, the method comprising the steps of: -providing a substrate; -forming a plug composed of plug material at said substrate; -forming a nanostructure (on or) at said plug; -forming a shell composed of at least one shell material on external surfaces of the nanostructure, with the at least one shell material covering said nanostructure and at least some of the plug material,whereby the shell and the plug encapsulate the nanostructure. The invention further relates to a coated nanostructure and to the use of a coated nanostructure.

pf

link (url) [BibTex]


no image
Influence Estimation and Maximization in Continuous-Time Diffusion Networks

Gomez-Rodriguez, M., Song, L., Du, N., Zha, H., Schölkopf, B.

ACM Transactions on Information Systems, 34(2):9:1-9:33, 2016 (article)

ei

DOI Project Page Project Page [BibTex]

DOI Project Page Project Page [BibTex]


Thumb xl heteroscedasticgp
Modeling Variability of Musculoskeletal Systems with Heteroscedastic Gaussian Processes

Büchler, D., Calandra, R., Peters, J.

Workshop on Neurorobotics, Neural Information Processing Systems (NIPS), 2016 (conference)

am ei

NIPS16Neurorobotics [BibTex]

NIPS16Neurorobotics [BibTex]


no image
Locally Weighted Regression for Control

Ting, J., Meier, F., Vijayakumar, S., Schaal, S.

In Encyclopedia of Machine Learning and Data Mining, pages: 1-14, Springer US, Boston, MA, 2016 (inbook)

am

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
The population of long-period transiting exoplanets

Foreman-Mackey, D., Morton, T. D., Hogg, D. W., Agol, E., Schölkopf, B.

The Astronomical Journal, 152(6):206, 2016 (article)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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

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

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

am ics

PDF DOI [BibTex]

PDF DOI [BibTex]


Thumb xl iser small
Generalizing Regrasping with Supervised Policy Learning

Chebotar, Y., Hausman, K., Kroemer, O., Sukhatme, G., Schaal, S.

In International Symposium on Experimental Robotics (ISER) 2016, International Symposium on Experimental Robotics, 2016 (inproceedings)

am

pdf video [BibTex]

pdf video [BibTex]


no image
Statistical source separation of rhythmic LFP patterns during sharp wave ripples in the macaque hippocampus

Ramirez-Villegas, J. F., Logothetis, N. K., Besserve, M.

47th Annual Meeting of the Society for Neuroscience (Neuroscience), 2016 (poster)

ei

[BibTex]

[BibTex]


no image
Screening Rules for Convex Problems

Raj, A., Olbrich, J., Gärtner, B., Schölkopf, B., Jaggi, M.

2016 (unpublished) Submitted

ei

[BibTex]

[BibTex]


no image
An overview of quantitative approaches in Gestalt perception

Jäkel, F., Singh, M., Wichmann, F. A., Herzog, M. H.

Vision Research, 126, pages: 3-8, 2016 (article)

ei

link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


no image
Causal and statistical learning

Schölkopf, B., Janzing, D., Lopez-Paz, D.

Oberwolfach Reports, 13(3):1896-1899, (Editors: A. Christmann and K. Jetter and S. Smale and D.-X. Zhou), 2016 (conference)

ei

DOI [BibTex]

DOI [BibTex]


no image
Bootstrat: Population Informed Bootstrapping for Rare Variant Tests

Huang, H., Peloso, G. M., Howrigan, D., Rakitsch, B., Simon-Gabriel, C. J., Goldstein, J. I., Daly, M. J., Borgwardt, K., Neale, B. M.

bioRxiv, 2016, preprint (article)

ei

link (url) DOI [BibTex]

link (url) DOI [BibTex]


no image
Probabilistic Movement Models Show that Postural Control Precedes and Predicts Volitional Motor Control

Rueckert, E., Camernik, J., Peters, J., Babic, J.

Nature PG: Scientific Reports, 6(Article number: 28455), 2016 (article)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


no image
Learning Taxonomy Adaptation in Large-scale Classification

Babbar, R., Partalas, I., Gaussier, E., Amini, M., Amblard, C.

Journal of Machine Learning Research, 17(98):1-37, 2016 (article)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


no image
Hippocampal neural events predict ongoing brain-wide BOLD activity

Besserve, M., Logothetis, N. K.

47th Annual Meeting of the Society for Neuroscience (Neuroscience), 2016 (poster)

ei

[BibTex]

[BibTex]


no image
BOiS—Berlin Object in Scene Database: Controlled Photographic Images for Visual Search Experiments with Quantified Contextual Priors

Mohr, J., Seyfarth, J., Lueschow, A., Weber, J. E., Wichmann, F. A., Obermayer, K.

Frontiers in Psychology, 2016 (article)

ei

DOI [BibTex]

DOI [BibTex]


no image
Preface to the ACM TIST Special Issue on Causal Discovery and Inference

Zhang, K., Li, J., Bareinboim, E., Schölkopf, B., Pearl, J.

ACM Transactions on Intelligent Systems and Technologies, 7(2):article no. 17, 2016 (article)

ei

DOI [BibTex]

DOI [BibTex]


no image
Recurrent Spiking Networks Solve Planning Tasks

Rueckert, E., Kappel, D., Tanneberg, D., Pecevski, D., Peters, J.

Nature PG: Scientific Reports, 6(Article number: 21142), 2016 (article)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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

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

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

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

am mg

link (url) DOI [BibTex]


no image
Inertial Sensor-Based Humanoid Joint State Estimation

Rotella, N., Mason, S., Schaal, S., Righetti, L.

In 2016 IEEE International Conference on Robotics and Automation (ICRA), pages: 1825-1831, IEEE, Stockholm, Sweden, 2016 (inproceedings)

Abstract
This work presents methods for the determination of a humanoid robot's joint velocities and accelerations directly from link-mounted Inertial Measurement Units (IMUs) each containing a three-axis gyroscope and a three-axis accelerometer. No information about the global pose of the floating base or its links is required and precise knowledge of the link IMU poses is not necessary due to presented calibration routines. Additionally, a filter is introduced to fuse gyroscope angular velocities with joint position measurements and compensate the computed joint velocities for time-varying gyroscope biases. The resulting joint velocities are subject to less noise and delay than filtered velocities computed from numerical differentiation of joint potentiometer signals, leading to superior performance in joint feedback control as demonstrated in experiments performed on a SARCOS hydraulic humanoid.

am mg

link (url) DOI [BibTex]

link (url) DOI [BibTex]