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2016


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Efficient Large-scale Approximate Nearest Neighbor Search on the GPU

Wieschollek, P., Wang, O., Sorkine-Hornung, A., Lensch, H. P. A.

29th IEEE Conference on Computer Vision and Pattern Recognition (CVPR), pages: 2027 - 2035, IEEE, June 2016 (conference)

ei

DOI [BibTex]

2016


DOI [BibTex]


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On the Identifiability and Estimation of Functional Causal Models in the Presence of Outcome-Dependent Selection

Zhang, K., Zhang, J., Huang, B., Schölkopf, B., Glymour, C.

Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence (UAI), pages: 825-834, (Editors: Ihler, A. and Janzing, D.), AUAI Press, June 2016 (conference)

ei

link (url) [BibTex]

link (url) [BibTex]


Thumb xl screen shot 2018 10 09 at 11.42.49
Active Uncertainty Calibration in Bayesian ODE Solvers

Kersting, H., Hennig, P.

Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence (UAI), pages: 309-318, (Editors: Ihler, A. and Janzing, D.), AUAI Press, June 2016 (conference)

Abstract
There is resurging interest, in statistics and machine learning, in solvers for ordinary differential equations (ODEs) that return probability measures instead of point estimates. Recently, Conrad et al.~introduced a sampling-based class of methods that are `well-calibrated' in a specific sense. But the computational cost of these methods is significantly above that of classic methods. On the other hand, Schober et al.~pointed out a precise connection between classic Runge-Kutta ODE solvers and Gaussian filters, which gives only a rough probabilistic calibration, but at negligible cost overhead. By formulating the solution of ODEs as approximate inference in linear Gaussian SDEs, we investigate a range of probabilistic ODE solvers, that bridge the trade-off between computational cost and probabilistic calibration, and identify the inaccurate gradient measurement as the crucial source of uncertainty. We propose the novel filtering-based method Bayesian Quadrature filtering (BQF) which uses Bayesian quadrature to actively learn the imprecision in the gradient measurement by collecting multiple gradient evaluations.

ei pn

link (url) Project Page Project Page [BibTex]

link (url) Project Page Project Page [BibTex]


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The Arrow of Time in Multivariate Time Serie

Bauer, S., Schölkopf, B., Peters, J.

Proceedings of the 33rd International Conference on Machine Learning (ICML), 48, pages: 2043-2051, JMLR Workshop and Conference Proceedings, (Editors: Balcan, M. F. and Weinberger, K. Q.), JMLR, June 2016 (conference)

ei

link (url) [BibTex]

link (url) [BibTex]


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A Kernel Test for Three-Variable Interactions with Random Processes

Rubenstein, P. K., Chwialkowski, K. P., Gretton, A.

Proceedings of the Thirty-Second Conference on Uncertainty in Artificial Intelligence (UAI), (Editors: Ihler, Alexander T. and Janzing, Dominik), June 2016 (conference)

ei

PDF Supplement Arxiv [BibTex]

PDF Supplement Arxiv [BibTex]


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Continuous Deep Q-Learning with Model-based Acceleration

Gu, S., Lillicrap, T., Sutskever, I., Levine, S.

Proceedings of the 33nd International Conference on Machine Learning (ICML), 48, pages: 2829-2838, JMLR Workshop and Conference Proceedings, (Editors: Maria-Florina Balcan and Kilian Q. Weinberger), JMLR.org, June 2016 (conference)

ei

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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Bounded Rational Decision-Making in Feedforward Neural Networks

Leibfried, F, Braun, D

Proceedings of the 32nd Conference on Uncertainty in Artificial Intelligence (UAI), pages: 407-416, June 2016 (conference)

Abstract
Bounded rational decision-makers transform sensory input into motor output under limited computational resources. Mathematically, such decision-makers can be modeled as information-theoretic channels with limited transmission rate. Here, we apply this formalism for the first time to multilayer feedforward neural networks. We derive synaptic weight update rules for two scenarios, where either each neuron is considered as a bounded rational decision-maker or the network as a whole. In the update rules, bounded rationality translates into information-theoretically motivated types of regularization in weight space. In experiments on the MNIST benchmark classification task for handwritten digits, we show that such information-theoretic regularization successfully prevents overfitting across different architectures and attains results that are competitive with other recent techniques like dropout, dropconnect and Bayes by backprop, for both ordinary and convolutional neural networks.

ei

[BibTex]

[BibTex]


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System and method to magnetically actuate a capsule endoscopic robot for diagnosis and treatment

Sitti, M., Yim, S.

May 2016, US Patent 9,445,711 (patent)

Abstract
Present invention describes a swallowable device with a soft, compliant exterior, whose shape can be changed through the use of magnetic fields, and which can be locomoted in a rolling motion through magnetic control from the exterior of the patient. The present invention could be used for a variety of medical applications inside the GI tract including but not limited to drug delivery, biopsy, heat cauterization, pH sensing, biochemical sensing, micro-surgery, and active imaging.

pi

link (url) [BibTex]


Thumb xl ye et al 2016 advanced materials
Gallium Adhesion: Phase Change of Gallium Enables Highly Reversible and Switchable Adhesion (Adv. Mater. 25/2016)

Ye, Z., Lum, G. Z., Song, S., Rich, S., Sitti, M.

Advanced Materials, 28(25):5087-5087, May 2016 (article)

Abstract
Gallium exhibits highly reversible and switchable adhesion when it undergoes a solid–liquid phase transition. The robustness of gallium is notable as it exhibits strong performance on a wide range of smooth and rough surfaces, under both dry and wet conditions. Gallium may therefore find numerous applications in transfer printing, robotics, electronic packaging, and biomedicine.

pi

DOI [BibTex]


Thumb xl singh et al 2016 advanced healthcare materials
Patterned and Specific Attachment of Bacteria on Biohybrid Bacteria-Driven Microswimmers

Singh, A. V., Sitti, M.

Advanced Healthcare Materials, 5(18):2325-2331, May 2016 (article)

Abstract
A surface patterning technique and a specific and strong biotin–streptavidin bonding of bacteria on patterned surfaces are proposed to fabricate Janus particles that are propelled by the attached bacteria. Bacteria-driven Janus microswimmers with diameters larger than 3 μm show enhanced mean propulsion speed. Such microswimmers could be used for future applications such as targeted drug delivery and environmental remediation.

pi

DOI [BibTex]


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Shape-programmable magnetic soft matter

Lum, G. Z., Ye, Z., Dong, X., Marvi, H., Erin, O., Hu, W., Sitti, M.

Proceedings of the National Academy of Sciences, 113(41):E6007–E6015, National Acad Sciences, May 2016 (article)

Abstract
Shape-programmable matter is a class of active materials whose geometry can be controlled to potentially achieve mechanical functionalities beyond those of traditional machines. Among these materials, magnetically actuated matter is particularly promising for achieving complex time-varying shapes at small scale (overall dimensions smaller than 1 cm). However, previous work can only program these materials for limited applications, as they rely solely on human intuition to approximate the required magnetization profile and actuating magnetic fields for their materials. Here, we propose a universal programming methodology that can automatically generate the required magnetization profile and actuating fields for soft matter to achieve new time-varying shapes. The universality of the proposed method can therefore inspire a vast number of miniature soft devices that are critical in robotics, smart engineering surfaces and materials, and biomedical devices. Our proposed method includes theoretical formulations, computational strategies, and fabrication procedures for programming magnetic soft matter. The presented theory and computational method are universal for programming 2D or 3D time-varying shapes, whereas the fabrication technique is generic only for creating planar beams. Based on the proposed programming method, we created a jellyfish-like robot, a spermatozoid-like undulating swimmer, and an artificial cilium that could mimic the complex beating patterns of its biological counterpart.

pi

DOI [BibTex]

DOI [BibTex]


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Sperm-shaped magnetic microrobots: Fabrication using electrospinning, modeling, and characterization

Khalil, I. S., Tabak, A. F., Hosney, A., Mohamed, A., Klingner, A., Ghoneima, M., Sitti, M.

In Robotics and Automation (ICRA), 2016 IEEE International Conference on, pages: 1939-1944, May 2016 (inproceedings)

Abstract
We use electrospinning to fabricate sperm-shaped magnetic microrobots with a range of diameters from 50 μm to 500 μm. The variables of the electrospinning operation (voltage, concentration of the solution, dynamic viscosity, and distance between the syringe needle and collector) to achieve beading effect are determined. This beading effect allows us to fabricate microrobots with similar morphology to that of sperm cells. The bead and the ultra-fine fiber resemble the morphology of the head and tail of the sperm cell, respectively. We incorporate iron oxide nanoparticles to the head of the sperm-shaped microrobot to provide a magnetic dipole moment. This dipole enables directional control under the influence of external magnetic fields. We also apply weak (less than 2 mT) oscillating magnetic fields to exert a magnetic torque on the magnetic head, and generate planar flagellar waves and flagellated swim. The average speed of the sperm-shaped microrobot is calculated to be 0.5 body lengths per second and 1 body lengths per second at frequencies of 5 Hz and 10 Hz, respectively. We also develop a model of the microrobot using elastohydrodynamics approach and Timoshenko-Rayleigh beam theory, and find good agreement with the experimental results.

pi

DOI [BibTex]

DOI [BibTex]


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Batch Bayesian Optimization via Local Penalization

González, J., Dai, Z., Hennig, P., Lawrence, N.

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), 51, pages: 648-657, JMLR Workshop and Conference Proceedings, (Editors: Gretton, A. and Robert, C. C.), May 2016 (conference)

ei pn

link (url) Project Page [BibTex]

link (url) Project Page [BibTex]


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MuProp: Unbiased Backpropagation for Stochastic Neural Networks

Gu, S., Levine, S., Sutskever, I., Mnih, A.

4th International Conference on Learning Representations (ICLR), May 2016 (conference)

ei

Arxiv [BibTex]

Arxiv [BibTex]


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An Improved Cognitive Brain-Computer Interface for Patients with Amyotrophic Lateral Sclerosis

Hohmann, M. R., Fomina, T., Jayaram, V., Förster, C., Just, J., M., S., Schölkopf, B., Schöls, L., Grosse-Wentrup, M.

Proceedings of the Sixth International BCI Meeting, pages: 44, (Editors: Müller-Putz, G. R. and Huggins, J. E. and Steyrl, D.), BCI, May 2016 (conference)

ei

DOI [BibTex]

DOI [BibTex]


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Autofocusing-based correction of B0 fluctuation-induced ghosting

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

24th Annual Meeting and Exhibition of the International Society for Magnetic Resonance in Medicine (ISMRM), May 2016 (poster)

ei

link (url) [BibTex]

link (url) [BibTex]


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Movement Primitives with Multiple Phase Parameters

Ewerton, M., Maeda, G., Neumann, G., Kisner, V., Kollegger, G., Wiemeyer, J., Peters, J.

IEEE International Conference on Robotics and Automation (ICRA), pages: 201-206, IEEE, May 2016 (conference)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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TerseSVM : A Scalable Approach for Learning Compact Models in Large-scale Classification

Babbar, R., Muandet, K., Schölkopf, B.

Proceedings of the 2016 SIAM International Conference on Data Mining (SDM), pages: 234-242, (Editors: Sanjay Chawla Venkatasubramanian and Wagner Meira), May 2016 (conference)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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A Lightweight Robotic Arm with Pneumatic Muscles for Robot Learning

Büchler, D., Ott, H., Peters, J.

Proceedings of the IEEE International Conference on Robotics and Automation (ICRA), pages: 4086-4092, IEEE, IEEE International Conference on Robotics and Automation, May 2016 (conference)

am ei

ICRA16final DOI Project Page [BibTex]

ICRA16final DOI Project Page [BibTex]


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Probabilistic Approximate Least-Squares

Bartels, S., Hennig, P.

Proceedings of the 19th International Conference on Artificial Intelligence and Statistics (AISTATS), 51, pages: 676-684, JMLR Workshop and Conference Proceedings, (Editors: Gretton, A. and Robert, C. C. ), May 2016 (conference)

Abstract
Least-squares and kernel-ridge / Gaussian process regression are among the foundational algorithms of statistics and machine learning. Famously, the worst-case cost of exact nonparametric regression grows cubically with the data-set size; but a growing number of approximations have been developed that estimate good solutions at lower cost. These algorithms typically return point estimators, without measures of uncertainty. Leveraging recent results casting elementary linear algebra operations as probabilistic inference, we propose a new approximate method for nonparametric least-squares that affords a probabilistic uncertainty estimate over the error between the approximate and exact least-squares solution (this is not the same as the posterior variance of the associated Gaussian process regressor). This allows estimating the error of the least-squares solution on a subset of the data relative to the full-data solution. The uncertainty can be used to control the computational effort invested in the approximation. Our algorithm has linear cost in the data-set size, and a simple formal form, so that it can be implemented with a few lines of code in programming languages with linear algebra functionality.

ei pn

link (url) Project Page Project Page [BibTex]

link (url) Project Page Project Page [BibTex]


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Learning soft task priorities for control of redundant robots

Modugno, V., Neumann, G., Rueckert, E., Oriolo, G., Peters, J., Ivaldi, S.

IEEE International Conference on Robotics and Automation (ICRA), pages: 221-226, IEEE, May 2016 (conference)

ei

DOI [BibTex]

DOI [BibTex]


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On the Reliability of Information and Trustworthiness of Web Sources in Wikipedia

Tabibian, B., Farajtabar, M., Valera, I., Song, L., Schölkopf, B., Gomez Rodriguez, M.

Wikipedia workshop at the 10th International AAAI Conference on Web and Social Media (ICWSM), May 2016 (conference)

ei

[BibTex]

[BibTex]


Thumb xl 2016 peer grading
Peer Grading in a Course on Algorithms and Data Structures: Machine Learning Algorithms do not Improve over Simple Baselines

Sajjadi, M. S. M., Alamgir, M., von Luxburg, U.

Proceedings of the 3rd ACM conference on Learning @ Scale, pages: 369-378, (Editors: Haywood, J. and Aleven, V. and Kay, J. and Roll, I.), ACM, L@S, April 2016, (An earlier version of this paper had been presented at the ICML 2015 workshop for Machine Learning for Education.) (conference)

ei

Arxiv Peer-Grading dataset request [BibTex]

Arxiv Peer-Grading dataset request [BibTex]


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Inflated soft actuators with reversible stable deformations

Hines, L., Petersen, K., Sitti, M.

Advanced Materials, 28(19):3690-3696, March 2016 (article)

Abstract
Most soft robotic systems are currently dependent on bulky compressors or pumps. A soft actuation method is presented combining hyperelastic membranes and dielectric elastomer actuators to switch between stable deformations of sealed chambers. This method is capable of large repeatable deformations, and has a number of stable states proportional to the number of actuatable membranes in the chamber.

pi

DOI Project Page [BibTex]


Thumb xl publications toc
Chemotaxis of bio-hybrid multiple bacteria-driven microswimmers

Zhuang, J., Sitti, M.

Scientific reports, 6, pages: 32135, Nature Publishing Group, March 2016 (article)

Abstract
In this study, in a bio-hybrid microswimmer system driven by multiple Serratia marcescens bacteria, we quantify the chemotactic drift of a large number of microswimmers towards L-serine and elucidate the associated collective chemotaxis behavior by statistical analysis of over a thousand swimming trajectories of the microswimmers. The results show that the microswimmers have a strong heading preference for moving up the L-serine gradient, while their speed does not change considerably when moving up and down the gradient; therefore, the heading bias constitutes the major factor that produces the chemotactic drift. The heading direction of a microswimmer is found to be significantly more persistent when it moves up the L-serine gradient than when it travels down the gradient; this effect causes the apparent heading preference of the microswimmers and is the crucial reason that enables the seemingly cooperative chemotaxis of multiple bacteria on a microswimmer. In addition, we find that their chemotactic drift velocity increases superquadratically with their mean swimming speed, suggesting that chemotaxis of bio-hybrid microsystems can be enhanced by designing and building faster microswimmers. Such bio-hybrid microswimmers with chemotactic steering capability may find future applications in targeted drug delivery, bioengineering, and lab-on-a-chip devices.

pi

DOI Project Page [BibTex]

DOI Project Page [BibTex]


Thumb xl publications toc
Targeted drug delivery and imaging using mobile milli/microrobots: A promising future towards theranostic pharmaceutical design

Vikram Singh, A., Sitti, M.

Current Pharmaceutical Design, 22(11):1418-1428, Bentham Science Publishers, March 2016 (article)

Abstract
Miniature untethered medical robots have been receiving growing attention due to technological advances in microactuation, microsensors, and microfabrication and have significant potential to reduce the invasiveness and improve the accessibility of medical devices into unprecedented small spaces inside the human body. In this review, we discuss therapeutic and diagnostic applications of untethered medical microrobots. Wirelessly controlled milli/microrobots with integrated sensors are revolutionizing micromanipulation based medical interventions and are enabling doctors to perform minimally invasive procedures not possible before. 3D fabrication technologies enabling milli/microrobot fabrication at the single cell scale are empowering high-resolution visual imaging and in vivo manipulation capabilities. Swallowable millirobots and injectabale ocular microrobots allow the gastric ulcer imaging, and performance of vitreoretinal microsurgery at previously inaccessible ocular sites. Many invasive excision and incision based diagnostic biopsy, prostrate, and nephrolgical procedures can be performed minimally or almost noninvasively due to recent advancements in microrobotic technology. Advances in biohybrid microrobot systems are pushing microrobotic systems even smaller, using biological cells as on-board microactuators and microsensors using the chemical energy. Such microrobotic systems could be used for local targeted delivery of imaging contrast agents, drugs, genes, and mRNA, minimally invasive surgery, and cell micromanipulation in the near future.

pi

link (url) [BibTex]


Thumb xl publications toc
Parallel microcracks-based ultrasensitive and highly stretchable strain sensors

Amjadi, M., Turan, M., Clementson, C. P., Sitti, M.

ACS Applied Materials \& Interfaces, 8(8):5618-5626, American Chemical Society, Febuary 2016 (article)

Abstract
There is an increasing demand for flexible, skin-attachable, and wearable strain sensors due to their various potential applications. However, achieving strain sensors with both high sensitivity and high stretchability is still a grand challenge. Here, we propose highly sensitive and stretchable strain sensors based on the reversible microcrack formation in composite thin films. Controllable parallel microcracks are generated in graphite thin films coated on elastomer films. Sensors made of graphite thin films with short microcracks possess high gauge factors (maximum value of 522.6) and stretchability (ε ≥ 50%), whereas sensors with long microcracks show ultrahigh sensitivity (maximum value of 11 344) with limited stretchability (ε ≤ 50%). We demonstrate the high performance strain sensing of our sensors in both small and large strain sensing applications such as human physiological activity recognition, human body large motion capturing, vibration detection, pressure sensing, and soft robotics.

pi

DOI [BibTex]

DOI [BibTex]


Thumb xl amjadi et al 2016 advanced functional materials
Stretchable, Skin-Mountable, and Wearable Strain Sensors and Their Potential Applications: A Review

Amjadi, M., Kyung, K., Park, I., Sitti, M.

Advanced Functional Materials, 26, pages: 1678-1698, Febuary 2016 (article)

Abstract
There is a growing demand for flexible and soft electronic devices. In particular, stretchable, skin-mountable, and wearable strain sensors are needed for several potential applications including personalized health-monitoring, human motion detection, human-machine interfaces, soft robotics, and so forth. This Feature Article presents recent advancements in the development of flexible and stretchable strain sensors. The article shows that highly stretchable strain sensors are successfully being developed by new mechanisms such as disconnection between overlapped nanomaterials, crack propagation in thin films, and tunneling effect, different from traditional strain sensing mechanisms. Strain sensing performances of recently reported strain sensors are comprehensively studied and discussed, showing that appropriate choice of composite structures as well as suitable interaction between functional nanomaterials and polymers are essential for the high performance strain sensing. Next, simulation results of piezoresistivity of stretchable strain sensors by computational models are reported. Finally, potential applications of flexible strain sensors are described. This survey reveals that flexible, skin-mountable, and wearable strain sensors have potential in diverse applications while several grand challenges have to be still overcome.

pi

DOI [BibTex]

DOI [BibTex]


Thumb xl toc image patent
Remotely addressable magnetic composite micro-actuators

Sitti, M., Diller, E., Miyashita, S.

Febuary 2016, US Patent App. 15/018,008 (patent)

Abstract
The present invention describes methods to fabricate actuators that can be remotely controlled in an addressable manner, and methods to provide remote control such micro-actuators. The actuators are composites of two permanent magnet materials, one of which is has high coercivity, and the other of which switches magnetization direction by applied fields. By switching the second material's magnetization direction, the two magnets either work together or cancel each other, resulting in distinct “on” and “off” behavior of the devices. The device can be switched “on” or “off” remotely using a field pulse of short duration.

pi

[BibTex]

[BibTex]


Thumb xl toc image patent
Remotely addressable magnetic composite micro-actuators

Sitti, M., Diller, E., Miyashita, S.

Febuary 2016, US Patent 9,281,112 (patent)

Abstract
The present invention describes methods to fabricate actuators that can be remotely controlled in an addressable manner, and methods to provide remote control such micro-actuators. The actuators are composites of two permanent magnet materials, one of which is has high coercivity, and the other of which switches magnetization direction by applied fields. By switching the second material's magnetization direction, the two magnets either work together or cancel each other, resulting in distinct “on” and “off” behavior of the devices. The device can be switched “on” or “off” remotely using a field pulse of short duration.

pi

link (url) [BibTex]

link (url) [BibTex]


Thumb xl b 07384529
Size optimization of a magnetic system for drug delivery with capsule robots

Munoz, F., Alici, G., Li, W., Sitti, M.

IEEE Transactions on Magnetics, 52(5):1-11, IEEE, January 2016 (article)

Abstract
In this paper, we present a methodology for the size optimization of an external magnetic system made of arc-shaped permanent magnets (ASMs). This magnetic system is able to remotely actuate a drug-release module embedded in a prototype of a capsule robot. The optimization of the magnetic system is carried out by using an accurate analytical model that is valid for any arbitrary dimensions of the ASMs. By using this analytical model, we perform parametric studies and conduct a statistical analysis [analysis of variance (ANOVA)] to investigate efficient ways to distribute the volume of the ASMs so that the dimensions and volume of the magnetic system are minimized while optimal flux densities and magnetic torques are obtained to actuate the drug delivery system (DDS). The ANOVA results, at 5% significance level, indicate that changes in the angular width followed by changes in the length of the ASMs have the highest impact on the magnetic linkage. Furthermore, our experimental results, which are in agreement with the analytical results, show that the size optimization of the magnetic system is effective for the actuation of the DDS in capsule robots.

pi

DOI [BibTex]

DOI [BibTex]


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On estimation of functional causal models: General results and application to post-nonlinear causal model

Zhang, K., Wang, Z., Zhang, J., Schölkopf, B.

ACM Transactions on Intelligent Systems and Technologies, 7(2):article no. 13, January 2016 (article)

ei

PDF DOI [BibTex]

PDF DOI [BibTex]


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Fabular: Regression Formulas As Probabilistic Programming

Borgström, J., Gordon, A. D., Ouyang, L., Russo, C., Ścibior, A., Szymczak, M.

Proceedings of the 43rd Annual ACM SIGPLAN-SIGACT Symposium on Principles of Programming Languages (POPL), pages: 271-283, POPL ’16, ACM, January 2016 (conference)

ei

DOI Project Page [BibTex]

DOI Project Page [BibTex]


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Special Issue on Causal Discovery and Inference

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

ACM Transactions on Intelligent Systems and Technology (TIST), 7(2), January 2016, (Guest Editors) (misc)

ei

[BibTex]

[BibTex]


Thumb xl cloud tracking
Gaussian Process-Based Predictive Control for Periodic Error Correction

Klenske, E. D., Zeilinger, M., Schölkopf, B., Hennig, P.

IEEE Transactions on Control Systems Technology , 24(1):110-121, 2016 (article)

ei pn

PDF DOI [BibTex]

PDF DOI [BibTex]


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Empirical Inference (2010-2015)
Scientific Advisory Board Report, 2016 (misc)

ei

pdf [BibTex]

pdf [BibTex]


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Pymanopt: A Python Toolbox for Optimization on Manifolds using Automatic Differentiation

Townsend, J., Koep, N., Weichwald, S.

Journal of Machine Learning Research, 17(137):1-5, 2016 (article)

ei

PDF Arxiv Code Project page link (url) [BibTex]


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A Causal, Data-driven Approach to Modeling the Kepler Data

Wang, D., Hogg, D. W., Foreman-Mackey, D., Schölkopf, B.

Publications of the Astronomical Society of the Pacific, 128(967):094503, 2016 (article)

ei

link (url) DOI Project Page [BibTex]

link (url) DOI Project Page [BibTex]


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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]

DOI Project Page [BibTex]


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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]


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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]


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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]


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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]


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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]


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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]


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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]


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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]