Publications | Empirical Inference - Max Planck Institute for Intelligent Systems

220 results (View BibTeX file of all listed publications)

2018

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)

2018

Lioutikov, R., Maeda, G., Veiga, F., Kersting, K., Peters, J. Inducing Probabilistic Context-Free Grammars for the Sequencing of Movement Primitives IEEE International Conference on Robotics and Automation, (ICRA), pages: 1-8, IEEE, May 2018 (conference)

DOI Project Page [BibTex]

Sobolev GAN

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

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

link (url) Project Page [BibTex]

Mroueh, Y., Li*, C., Sercu*, T., Raj*, A., Cheng, Y. Sobolev GAN 6th International Conference on Learning Representations (ICLR), May 2018, *equal contribution (conference)

link (url) Project Page [BibTex]

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)

link (url) Project Page [BibTex]

Pong*, V., Gu*, S., Dalal, M., Levine, S. Temporal Difference Models: Model-Free Deep RL for Model-Based Control 6th International Conference on Learning Representations (ICLR), May 2018, *equal contribution (conference)

link (url) Project Page [BibTex]

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)

link (url) Project Page [BibTex]

Rubenstein, P. K., Schölkopf, B., Tolstikhin, I. Wasserstein Auto-Encoders: Latent Dimensionality and Random Encoders Workshop at the 6th International Conference on Learning Representations (ICLR), May 2018 (conference)

link (url) Project Page [BibTex]

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)

Videos link (url) Project Page [BibTex]

Eysenbach, B., Gu, S., Ibarz, J., Levine, S. Leave no Trace: Learning to Reset for Safe and Autonomous Reinforcement Learning 6th International Conference on Learning Representations (ICLR), May 2018 (conference)

Videos link (url) Project Page [BibTex]

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)

arXiv [BibTex]

Sajjadi, M. S. M., Parascandolo, G., Mehrjou, A., Schölkopf, B. Tempered Adversarial Networks Workshop at the 6th International Conference on Learning Representations (ICLR), May 2018 (conference)

arXiv [BibTex]

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)

DOI Project Page [BibTex]

Koert, D., Maeda, G., Neumann, G., Peters, J. Learning Coupled Forward-Inverse Models with Combined Prediction Errors IEEE International Conference on Robotics and Automation, (ICRA), pages: 2433-2439, IEEE, May 2018 (conference)

DOI Project Page [BibTex]

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)

link (url) Project Page [BibTex]

Rubenstein, P. K., Schölkopf, B., Tolstikhin, I. Learning Disentangled Representations with Wasserstein Auto-Encoders Workshop at the 6th International Conference on Learning Representations (ICLR), May 2018 (conference)

link (url) Project Page [BibTex]

Automatic Estimation of Modulation Transfer Functions

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

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

DOI [BibTex]

Bauer, M., Volchkov, V., Hirsch, M., Schölkopf, B. Automatic Estimation of Modulation Transfer Functions IEEE International Conference on Computational Photography (ICCP), May 2018 (conference)

DOI [BibTex]

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)

link (url) [BibTex]

Rojas-Carulla, M., Baroni, M., Lopez-Paz, D. Causal Discovery Using Proxy Variables Workshop at 6th International Conference on Learning Representations (ICLR), May 2018 (conference)

link (url) [BibTex]

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)

DOI Project Page [BibTex]

Pinsler, R., Akrour, R., Osa, T., Peters, J., Neumann, G. Sample and Feedback Efficient Hierarchical Reinforcement Learning from Human Preferences IEEE International Conference on Robotics and Automation, (ICRA), pages: 596-601, IEEE, May 2018 (conference)

DOI Project Page [BibTex]

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)

link (url) [BibTex]

Besserve, M., Shajarisales, N., Schölkopf, B., Janzing, D. Group invariance principles for causal generative models 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)

link (url) [BibTex]

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)

link (url) Project Page Project Page [BibTex]

Locatello, F., Khanna, R., Ghosh, J., Rätsch, G. Boosting Variational Inference: an Optimization Perspective 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)

link (url) Project Page Project Page [BibTex]

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)

link (url) [BibTex]

Blöbaum, P., Janzing, D., Washio, T., Shimizu, S., Schölkopf, B. Cause-Effect Inference by Comparing Regression Errors 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)

link (url) [BibTex]

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)

DOI [BibTex]

Schwarz, K., Wieschollek, P., Lensch, H. P. A. Will People Like Your Image? Learning the Aesthetic Space 2018 IEEE Winter Conference on Applications of Computer Vision (WACV), pages: 2048-2057, March 2018 (conference)

DOI [BibTex]

Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation

Kim, J., Tabibian, B., Oh, A., Schölkopf, B., Gomez Rodriguez, M.

Proceedings of the 11th ACM International Conference on Web Search and Data Mining (WSDM), pages: 324-332, (Editors: Yi Chang, Chengxiang Zhai, Yan Liu, and Yoelle Maarek), ACM, Febuary 2018 (conference)

DOI Project Page Project Page [BibTex]

Kim, J., Tabibian, B., Oh, A., Schölkopf, B., Gomez Rodriguez, M. Leveraging the Crowd to Detect and Reduce the Spread of Fake News and Misinformation Proceedings of the 11th ACM International Conference on Web Search and Data Mining (WSDM), pages: 324-332, (Editors: Yi Chang, Chengxiang Zhai, Yan Liu, and Yoelle Maarek), ACM, Febuary 2018 (conference)

DOI Project Page Project Page [BibTex]

Functional Programming for Modular Bayesian Inference

Ścibior, A., Kammar, O., Ghahramani, Z.

Proceedings of the ACM on Functional Programming (ICFP), 2(Article No. 83):1-29, ACM, 2018 (conference)

DOI Project Page [BibTex]

Ścibior, A., Kammar, O., Ghahramani, Z. Functional Programming for Modular Bayesian Inference Proceedings of the ACM on Functional Programming (ICFP), 2(Article No. 83):1-29, ACM, 2018 (conference)

DOI Project Page [BibTex]

Automatic Bayesian Density Analysis

Vergari, A., Molina, A., Peharz, R., Ghahramani, Z., Kersting, K., Valera, I.

2018 (conference) Submitted

arXiv [BibTex]

Vergari, A., Molina, A., Peharz, R., Ghahramani, Z., Kersting, K., Valera, I. Automatic Bayesian Density Analysis 2018 (conference) Submitted

arXiv [BibTex]

Magic Tunnels

Kilcher*, Y., Becigneul*, G., Hofmann, T.

ICLR 2019, 2018, *equal contribution (conference) Submitted

[BibTex]

Kilcher*, Y., Becigneul*, G., Hofmann, T. Magic Tunnels ICLR 2019, 2018, *equal contribution (conference) Submitted

[BibTex]

Adversarial Extreme Multi-label Classification

Babbar, R., Schölkopf, B.

2018 (conference) Submitted

[BibTex]

Babbar, R., Schölkopf, B. Adversarial Extreme Multi-label Classification 2018 (conference) Submitted

[BibTex]

k–SVRG: Variance Reduction for Large Scale Optimization

Raj, A., Stich, S.

In 2018 (inproceedings) Submitted

[BibTex]

Raj, A., Stich, S. k–SVRG: Variance Reduction for Large Scale Optimization In 2018 (inproceedings) Submitted

[BibTex]

Probabilistic Deep Learning using Random Sum-Product Networks

Peharz, R., Vergari, A., Stelzner, K., Molina, A., Trapp, M., Kersting, K., Ghahramani, Z.

2018 (conference) Submitted

arXiv [BibTex]

Peharz, R., Vergari, A., Stelzner, K., Molina, A., Trapp, M., Kersting, K., Ghahramani, Z. Probabilistic Deep Learning using Random Sum-Product Networks 2018 (conference) Submitted

arXiv [BibTex]

A Differentially Private Kernel Two-Sample Test

Raj*, A., Law*, L., Sejdinovic*, D., Park, M.

2018, *equal contribution (conference) Submitted

[BibTex]

Raj*, A., Law*, L., Sejdinovic*, D., Park, M. A Differentially Private Kernel Two-Sample Test 2018, *equal contribution (conference) Submitted

[BibTex]

Counterfactuals uncover the modular structure of deep generative models

Besserve, M., Sun, R., Schölkopf, B.

2018 (conference) Submitted

[BibTex]

Besserve, M., Sun, R., Schölkopf, B. Counterfactuals uncover the modular structure of deep generative models 2018 (conference) Submitted

[BibTex]

Riemannian Adaptive Optimization Methods

Becigneul, G., Ganea, O.

ICLR 2019, 2018 (conference) Submitted

[BibTex]

Becigneul, G., Ganea, O. Riemannian Adaptive Optimization Methods ICLR 2019, 2018 (conference) Submitted

[BibTex]

Denotational Validation of Higher-order Bayesian Inference

Ścibior, A., Kammar, O., Vákár, M., Staton, S., Yang, H., Cai, Y., Ostermann, K., Moss, S. K., Heunen, C., Ghahramani, Z.

Proceedings of the ACM on Principles of Programming Languages (POPL), 2(Article No. 60):1-29, ACM, 2018 (conference)

DOI Project Page [BibTex]

Ścibior, A., Kammar, O., Vákár, M., Staton, S., Yang, H., Cai, Y., Ostermann, K., Moss, S. K., Heunen, C., Ghahramani, Z. Denotational Validation of Higher-order Bayesian Inference Proceedings of the ACM on Principles of Programming Languages (POPL), 2(Article No. 60):1-29, ACM, 2018 (conference)

DOI Project Page [BibTex]

Poincaré GloVe: Hyperbolic Word Embeddings

Tifrea*, A., Becigneul*, G., Ganea*, O.

ICLR 2019, 2018, *equal contribution (conference) Submitted

[BibTex]

Tifrea*, A., Becigneul*, G., Ganea*, O. Poincaré GloVe: Hyperbolic Word Embeddings ICLR 2019, 2018, *equal contribution (conference) Submitted

[BibTex]

2014

Human Pose Estimation with Fields of Parts

Kiefel, M., Gehler, P.

In Computer Vision – ECCV 2014, LNCS 8693, pages: 331-346, Lecture Notes in Computer Science, (Editors: Fleet, David and Pajdla, Tomas and Schiele, Bernt and Tuytelaars, Tinne), Springer, 13th European Conference on Computer Vision, September 2014 (inproceedings)

Abstract

This paper proposes a new formulation of the human pose estimation problem. We present the Fields of Parts model, a binary Conditional Random Field model designed to detect human body parts of articulated people in single images. The Fields of Parts model is inspired by the idea of Pictorial Structures, it models local appearance and joint spatial configuration of the human body. However the underlying graph structure is entirely different. The idea is simple: we model the presence and absence of a body part at every possible position, orientation, and scale in an image with a binary random variable. This results into a vast number of random variables, however, we show that approximate inference in this model is efficient. Moreover we can encode the very same appearance and spatial structure as in Pictorial Structures models. This approach allows us to combine ideas from segmentation and pose estimation into a single model. The Fields of Parts model can use evidence from the background, include local color information, and it is connected more densely than a kinematic chain structure. On the challenging Leeds Sports Poses dataset we improve over the Pictorial Structures counterpart by 5.5% in terms of Average Precision of Keypoints (APK).

website pdf DOI Project Page [BibTex]

2014

Kiefel, M., Gehler, P. Human Pose Estimation with Fields of Parts In Computer Vision – ECCV 2014, LNCS 8693, pages: 331-346, Lecture Notes in Computer Science, (Editors: Fleet, David and Pajdla, Tomas and Schiele, Bernt and Tuytelaars, Tinne), Springer, 13th European Conference on Computer Vision, September 2014 (inproceedings)

website pdf DOI Project Page [BibTex]

Probabilistic Progress Bars

Kiefel, M., Schuler, C., Hennig, P.

In Conference on Pattern Recognition (GCPR), 8753, pages: 331-341, Lecture Notes in Computer Science, (Editors: Jiang, X., Hornegger, J., and Koch, R.), Springer, GCPR, September 2014 (inproceedings)

Abstract

Predicting the time at which the integral over a stochastic process reaches a target level is a value of interest in many applications. Often, such computations have to be made at low cost, in real time. As an intuitive example that captures many features of this problem class, we choose progress bars, a ubiquitous element of computer user interfaces. These predictors are usually based on simple point estimators, with no error modelling. This leads to fluctuating behaviour confusing to the user. It also does not provide a distribution prediction (risk values), which are crucial for many other application areas. We construct and empirically evaluate a fast, constant cost algorithm using a Gauss-Markov process model which provides more information to the user.

website+code pdf DOI [BibTex]

Kiefel, M., Schuler, C., Hennig, P. Probabilistic Progress Bars In Conference on Pattern Recognition (GCPR), 8753, pages: 331-341, Lecture Notes in Computer Science, (Editors: Jiang, X., Hornegger, J., and Koch, R.), Springer, GCPR, September 2014 (inproceedings)

website+code pdf DOI [BibTex]

Seeing the Arrow of Time

Pickup, L., Zheng, P., Donglai, W., YiChang, S., Changshui, Z., Zisserman, A., Schölkopf, B., Freeman, W.

Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on, pages: 2043-2050, IEEE, CVPR, June 2014 (conference)

DOI [BibTex]

Pickup, L., Zheng, P., Donglai, W., YiChang, S., Changshui, Z., Zisserman, A., Schölkopf, B., Freeman, W. Seeing the Arrow of Time Computer Vision and Pattern Recognition (CVPR), 2014 IEEE Conference on, pages: 2043-2050, IEEE, CVPR, June 2014 (conference)

DOI [BibTex]

Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics

Hennig, P., Hauberg, S.

In Proceedings of the 17th International Conference on Artificial Intelligence and Statistics, 33, pages: 347-355, JMLR: Workshop and Conference Proceedings, (Editors: S Kaski and J Corander), Microtome Publishing, Brookline, MA, AISTATS, April 2014 (inproceedings)

Abstract

We study a probabilistic numerical method for the solution of both boundary and initial value problems that returns a joint Gaussian process posterior over the solution. Such methods have concrete value in the statistics on Riemannian manifolds, where non-analytic ordinary differential equations are involved in virtually all computations. The probabilistic formulation permits marginalising the uncertainty of the numerical solution such that statistics are less sensitive to inaccuracies. This leads to new Riemannian algorithms for mean value computations and principal geodesic analysis. Marginalisation also means results can be less precise than point estimates, enabling a noticeable speed-up over the state of the art. Our approach is an argument for a wider point that uncertainty caused by numerical calculations should be tracked throughout the pipeline of machine learning algorithms.

pdf Youtube Supplements Project page link (url) [BibTex]

Hennig, P., Hauberg, S. Probabilistic Solutions to Differential Equations and their Application to Riemannian Statistics In Proceedings of the 17th International Conference on Artificial Intelligence and Statistics, 33, pages: 347-355, JMLR: Workshop and Conference Proceedings, (Editors: S Kaski and J Corander), Microtome Publishing, Brookline, MA, AISTATS, April 2014 (inproceedings)

pdf Youtube Supplements Project page link (url) [BibTex]

A Visual Analytics Approach to Study Anatomic Covariation

Hermann, M., Schunke, A., Schultz, T., Klein, R.

In Proceedings of IEEE Pacific Visualization 2014, pages: 161-168, March 2014 (inproceedings)

Abstract

Gaining insight into anatomic covariation helps the understanding of organismic shape variability in general and is of particular interest for delimiting morphological modules. Generation of hypotheses on structural covariation is undoubtedly a highly creative process, and as such, requires an exploratory approach. In this work we propose a new local anatomic covariance tensor which enables interactive visualizations to explore covariation at different levels of detail, stimulating rapid formation and (qualitative) evaluation of hypotheses. The effectiveness of the presented approach is demonstrated on a muCT dataset of mouse mandibles for which results from the literature are successfully reproduced, while providing a more detailed representation of covariation compared to state-of-the-art methods.

PDF DOI [BibTex]

Hermann, M., Schunke, A., Schultz, T., Klein, R. A Visual Analytics Approach to Study Anatomic Covariation In Proceedings of IEEE Pacific Visualization 2014, pages: 161-168, March 2014 (inproceedings)

PDF DOI [BibTex]

Multi-Task Feature Selection on Multiple Networks via Maximum Flows

Sugiyama, M., Azencott, C., Grimm, D., Kawahara, Y., Borgwardt, K.

In Proceedings of the 2014 SIAM International Conference on Data Mining , pages: 199-207, SIAM, 2014 (inproceedings)

Web PDF DOI [BibTex]

Sugiyama, M., Azencott, C., Grimm, D., Kawahara, Y., Borgwardt, K. Multi-Task Feature Selection on Multiple Networks via Maximum Flows In Proceedings of the 2014 SIAM International Conference on Data Mining , pages: 199-207, SIAM, 2014 (inproceedings)

Web PDF DOI [BibTex]

Quantifying Information Overload in Social Media and its Impact on Social Contagions

Gomez Rodriguez, M., Gummadi, K., Schölkopf, B.

In Proceedings of the Eighth International Conference on Weblogs and Social Media, pages: 170-179, (Editors: E. Adar, P. Resnick, M. De Choudhury, B. Hogan, and A. Oh), AAAI Press, ICWSM, 2014 (inproceedings)

Web [BibTex]

Gomez Rodriguez, M., Gummadi, K., Schölkopf, B. Quantifying Information Overload in Social Media and its Impact on Social Contagions In Proceedings of the Eighth International Conference on Weblogs and Social Media, pages: 170-179, (Editors: E. Adar, P. Resnick, M. De Choudhury, B. Hogan, and A. Oh), AAAI Press, ICWSM, 2014 (inproceedings)

Web [BibTex]

Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm

Daneshmand, H., Gomez Rodriguez, M., Song, L., Schölkopf, B.

In Proceedings of the 31st International Conference on Machine Learning, W&CP 32 (1), pages: 793-801, (Editors: Eric P. Xing and Tony Jebara), JMLR, ICML, 2014 (inproceedings)

PDF [BibTex]

Daneshmand, H., Gomez Rodriguez, M., Song, L., Schölkopf, B. Estimating Diffusion Network Structures: Recovery Conditions, Sample Complexity & Soft-thresholding Algorithm In Proceedings of the 31st International Conference on Machine Learning, W&CP 32 (1), pages: 793-801, (Editors: Eric P. Xing and Tony Jebara), JMLR, ICML, 2014 (inproceedings)

PDF [BibTex]

Interaction Primitives for Human-Robot Cooperation Tasks

Ben Amor, H., Neumann, G., Kamthe, S., Kroemer, O., Peters, J.

In Proceedings of 2014 IEEE International Conference on Robotics and Automation, pages: 2831-2837, IEEE, ICRA, 2014 (inproceedings)

PDF DOI [BibTex]

Ben Amor, H., Neumann, G., Kamthe, S., Kroemer, O., Peters, J. Interaction Primitives for Human-Robot Cooperation Tasks In Proceedings of 2014 IEEE International Conference on Robotics and Automation, pages: 2831-2837, IEEE, ICRA, 2014 (inproceedings)

PDF DOI [BibTex]

Learning to Predict Phases of Manipulation Tasks as Hidden States

Kroemer, O., van Hoof, H., Neumann, G., Peters, J.

In Proceedings of 2014 IEEE International Conference on Robotics and Automation, pages: 4009-4014, IEEE, ICRA, 2014 (inproceedings)

PDF DOI [BibTex]

Kroemer, O., van Hoof, H., Neumann, G., Peters, J. Learning to Predict Phases of Manipulation Tasks as Hidden States In Proceedings of 2014 IEEE International Conference on Robotics and Automation, pages: 4009-4014, IEEE, ICRA, 2014 (inproceedings)

PDF DOI [BibTex]

Visualizing Uncertainty in HARDI Tractography Using Superquadric Streamtubes

Wiens, V., Schlaffke, L., Schmidt-Wilcke, T., Schultz, T.

In Eurographics Conference on Visualization, Short Papers, (Editors: Elmqvist, N. and Hlawitschka, M. and Kennedy, J.), EuroVis, 2014 (inproceedings)

Abstract

Standard streamtubes for the visualization of diffusion MRI data are rendered either with a circular or with an elliptic cross section whose aspect ratio indicates the relative magnitudes of the medium and minor eigenvalues. Inspired by superquadric tensor glyphs, we propose to render streamtubes with a superquadric cross section, which develops sharp edges to more clearly convey the orientation of the second and third eigenvectors where they are uniquely defined, while maintaining a circular shape when the smaller two eigenvalues are equal. As a second contribution, we apply our novel superquadric streamtubes to visualize uncertainty in the tracking direction of HARDI tractography, which we represent using a novel propagation uncertainty tensor.

link (url) DOI [BibTex]

Wiens, V., Schlaffke, L., Schmidt-Wilcke, T., Schultz, T. Visualizing Uncertainty in HARDI Tractography Using Superquadric Streamtubes In Eurographics Conference on Visualization, Short Papers, (Editors: Elmqvist, N. and Hlawitschka, M. and Kennedy, J.), EuroVis, 2014 (inproceedings)

link (url) DOI [BibTex]

A Permutation-Based Kernel Conditional Independence Test

Doran, G., Muandet, K., Zhang, K., Schölkopf, B.

In Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence (UAI2014), pages: 132-141, (Editors: Nevin L. Zhang and Jin Tian), AUAI Press Corvallis, Oregon, UAI2014, 2014 (inproceedings)

PDF [BibTex]

Doran, G., Muandet, K., Zhang, K., Schölkopf, B. A Permutation-Based Kernel Conditional Independence Test In Proceedings of the 30th Conference on Uncertainty in Artificial Intelligence (UAI2014), pages: 132-141, (Editors: Nevin L. Zhang and Jin Tian), AUAI Press Corvallis, Oregon, UAI2014, 2014 (inproceedings)

PDF [BibTex]

A unifying view of representer theorems

Argyriou, A., Dinuzzo, F.

In Proceedings of the 31th International Conference on Machine Learning, 32, pages: 748-756, (Editors: Xing, E. P. and Jebera, T.), ICML, 2014 (inproceedings)

PDF PDF [BibTex]

Argyriou, A., Dinuzzo, F. A unifying view of representer theorems In Proceedings of the 31th International Conference on Machine Learning, 32, pages: 748-756, (Editors: Xing, E. P. and Jebera, T.), ICML, 2014 (inproceedings)

PDF PDF [BibTex]

Riemannian Sparse Coding for Positive Definite Matrices

Cherian, A., Sra, S.

In 13th European Conference on Computer Vision, LNCS 8691, pages: 299-314, (Editors: Fleet, D., Pajdla, T., Schiele, B., and Tuytelaars, T.), Springer, ECCV, 2014 (inproceedings)

DOI [BibTex]

Cherian, A., Sra, S. Riemannian Sparse Coding for Positive Definite Matrices In 13th European Conference on Computer Vision, LNCS 8691, pages: 299-314, (Editors: Fleet, D., Pajdla, T., Schiele, B., and Tuytelaars, T.), Springer, ECCV, 2014 (inproceedings)

DOI [BibTex]

Probabilistic ODE Solvers with Runge-Kutta Means

Schober, M., Duvenaud, D., Hennig, P.

In Advances in Neural Information Processing Systems 27, pages: 739-747, (Editors: Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence and K.Q. Weinberger), Curran Associates, Inc., 28th Annual Conference on Neural Information Processing Systems (NIPS), 2014 (inproceedings)

Web link (url) [BibTex]

Schober, M., Duvenaud, D., Hennig, P. Probabilistic ODE Solvers with Runge-Kutta Means In Advances in Neural Information Processing Systems 27, pages: 739-747, (Editors: Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence and K.Q. Weinberger), Curran Associates, Inc., 28th Annual Conference on Neural Information Processing Systems (NIPS), 2014 (inproceedings)

Web link (url) [BibTex]

Mask-Specific Inpainting with Deep Neural Networks

Köhler, R., Schuler, C., Schölkopf, B., Harmeling, S.

In Pattern Recognition (GCPR 2014), pages: 523-534, (Editors: X Jiang, J Hornegger, and R Koch), Springer, 2014, Lecture Notes in Computer Science (inproceedings)

PDF DOI [BibTex]

Köhler, R., Schuler, C., Schölkopf, B., Harmeling, S. Mask-Specific Inpainting with Deep Neural Networks In Pattern Recognition (GCPR 2014), pages: 523-534, (Editors: X Jiang, J Hornegger, and R Koch), Springer, 2014, Lecture Notes in Computer Science (inproceedings)

PDF DOI [BibTex]

Randomized Nonlinear Component Analysis

Lopez-Paz, D., Sra, S., Smola, A., Ghahramani, Z., Schölkopf, B.

In Proceedings of the 31st International Conference on Machine Learning, W&CP 32 (1), pages: 1359-1367, (Editors: Eric P. Xing and Tony Jebara), JMLR, ICML, 2014 (inproceedings)

PDF [BibTex]

Lopez-Paz, D., Sra, S., Smola, A., Ghahramani, Z., Schölkopf, B. Randomized Nonlinear Component Analysis In Proceedings of the 31st International Conference on Machine Learning, W&CP 32 (1), pages: 1359-1367, (Editors: Eric P. Xing and Tony Jebara), JMLR, ICML, 2014 (inproceedings)

PDF [BibTex]

Causal and Anti-Causal Learning in Pattern Recognition for Neuroimaging

Weichwald, S., Schölkopf, B., Ball, T., Grosse-Wentrup, M.

In 4th International Workshop on Pattern Recognition in Neuroimaging (PRNI), IEEE , PRNI, 2014 (inproceedings)

PDF Arxiv DOI [BibTex]

Weichwald, S., Schölkopf, B., Ball, T., Grosse-Wentrup, M. Causal and Anti-Causal Learning in Pattern Recognition for Neuroimaging In 4th International Workshop on Pattern Recognition in Neuroimaging (PRNI), IEEE , PRNI, 2014 (inproceedings)

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Bayesian Gait Optimization for Bipedal Locomotion

Calandra, R., Gopalan, N., Seyfarth, A., Peters, J., Deisenroth, M.

In Proceedings of the 8th International Conference on Learning and Intelligent Optimization , LNCS 8426, pages: 274-290, Lecture Notes in Computer Science, (Editors: Pardalos, PM., Resende, MGC., Vogiatzis, C., and Walteros, JL.), Springer, LION, 2014 (inproceedings)

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Calandra, R., Gopalan, N., Seyfarth, A., Peters, J., Deisenroth, M. Bayesian Gait Optimization for Bipedal Locomotion In Proceedings of the 8th International Conference on Learning and Intelligent Optimization , LNCS 8426, pages: 274-290, Lecture Notes in Computer Science, (Editors: Pardalos, PM., Resende, MGC., Vogiatzis, C., and Walteros, JL.), Springer, LION, 2014 (inproceedings)

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Learning Manipulation by Sequencing Motor Primitives with a Two-Armed Robot

Lioutikov, R., Kroemer, O., Peters, J., Maeda, G.

In Proceedings of the 13th International Conference on Intelligent Autonomous Systems, 302, pages: 1601-1611, Advances in Intelligent Systems and Computing, (Editors: Menegatti, E., Michael, N., Berns, K., Yamaguchi, H.), Springer, IAS, 2014 (inproceedings)

DOI [BibTex]

Lioutikov, R., Kroemer, O., Peters, J., Maeda, G. Learning Manipulation by Sequencing Motor Primitives with a Two-Armed Robot In Proceedings of the 13th International Conference on Intelligent Autonomous Systems, 302, pages: 1601-1611, Advances in Intelligent Systems and Computing, (Editors: Menegatti, E., Michael, N., Berns, K., Yamaguchi, H.), Springer, IAS, 2014 (inproceedings)

DOI [BibTex]

Kernel Mean Estimation via Spectral Filtering

Muandet, K., Sriperumbudur, B., Schölkopf, B.

In Advances in Neural Information Processing Systems 27, pages: 1-9, (Editors: Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence and K.Q. Weinberger), Curran Associates, Inc., 28th Annual Conference on Neural Information Processing Systems (NIPS), 2014 (inproceedings)

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Muandet, K., Sriperumbudur, B., Schölkopf, B. Kernel Mean Estimation via Spectral Filtering In Advances in Neural Information Processing Systems 27, pages: 1-9, (Editors: Z. Ghahramani, M. Welling, C. Cortes, N.D. Lawrence and K.Q. Weinberger), Curran Associates, Inc., 28th Annual Conference on Neural Information Processing Systems (NIPS), 2014 (inproceedings)

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Shaping Social Activity by Incentivizing Users

Farajtabar, M., Du, N., Gomez Rodriguez, M., Valera, I., Zha, H., Song, L.

In Advances in Neural Information Processing Systems 27, (Editors: Ghahramani, Z., Welling, M., Cortes, C., Lawrence, ND., and Weinberger, KQ.), Curran Associates, Inc., 28th Annual Conference on Neural Information Processing Systems (NIPS), 2014 (inproceedings)

Web link (url) [BibTex]

Farajtabar, M., Du, N., Gomez Rodriguez, M., Valera, I., Zha, H., Song, L. Shaping Social Activity by Incentivizing Users In Advances in Neural Information Processing Systems 27, (Editors: Ghahramani, Z., Welling, M., Cortes, C., Lawrence, ND., and Weinberger, KQ.), Curran Associates, Inc., 28th Annual Conference on Neural Information Processing Systems (NIPS), 2014 (inproceedings)

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Consistency of Causal Inference under the Additive Noise Model

Kpotufe, S., Sgouritsa, E., Janzing, D., Schölkopf, B.

In Proceedings of the 31st International Conference on Machine Learning, W&CP 32 (1), pages: 478-495, (Editors: Eric P. Xing and Tony Jebara), JMLR, ICML, 2014 (inproceedings)

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Kpotufe, S., Sgouritsa, E., Janzing, D., Schölkopf, B. Consistency of Causal Inference under the Additive Noise Model In Proceedings of the 31st International Conference on Machine Learning, W&CP 32 (1), pages: 478-495, (Editors: Eric P. Xing and Tony Jebara), JMLR, ICML, 2014 (inproceedings)

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