Events & Talks

Intelligent Control Systems Talk Mona Buisson-Fenet 01-10-2018 Private Federated Learning With the expanding collection of data, organisations are becoming more and more aware of the potential gain of combining their data. Analytic and predictive tasks, such as classification, perform more accurately if more features or more data records are available, which is why data providers have an interest in joining their datasets and learning from the obtained database. However, this rising interest for federated learning also comes with an increasing concern about security and privacy, both from the consumers whose data is used, and from the data providers who are liable for protecting... Sebastian Trimpe

Theory of Inhomogeneous Condensed Matter Event 28-09-2018 Alexander Sattler, Universität Stuttgart Siegfried Dietrich

Theory of Inhomogeneous Condensed Matter Event 28-09-2018 Tim Meiler, Universität Stuttgart Siegfried Dietrich

Theory of Inhomogeneous Condensed Matter Event 27-09-2018 Moritz Wilke, Universität Stuttgart Siegfried Dietrich

Theory of Inhomogeneous Condensed Matter Event 27-09-2018 Rick Bebon, Universität Stuttgart

Physical Intelligence Talk Dr. Aude Bolopion and Dr. Mich 24-09-2018 Dexterous and non contact micromanipulation for micro-nano-assembly and biomedical applications This talk presents an overview of recent activities of FEMTO-ST institute in the field of micro-nanomanipulation fo both micro nano assembly and biomedical applications. Microrobotic systems are currently limited by the number of degree of freedom addressed and also are very limited by their throughput. Two ways can be considered to improve both the velocity and the degrees of freedom: non-contact manipulation and dexterous micromanipulation. Indeed in both ways movement including rotation and translation are done locally and are only limited by the micro-nano-objects inertia which is very ...

Perceiving Systems Talk Iasonas Kokkinos 24-09-2018 Learning to align images and surfaces In this talk I will be presenting recent work on combining ideas from deformable models with deep learning. I will start by describing DenseReg and DensePose, two recently introduced systems for establishing dense correspondences between 2D images and 3D surface models ``in the wild'', namely in the presence of background, occlusions, and multiple objects. For DensePose in particular we introduce DensePose-COCO, a large-scale dataset for dense pose estimation, and DensePose-RCNN, a system which operates at multiple frames per second on a single GPU while handling multiple humans simultaneo... Vassilis Choutas

Event 18-09-2018 - 20-09-2018 Special Symposium on Intelligent Systems 2018 Special Symposium on Intelligent Systems 2018 Michael Black Metin Sitti

Event 15-09-2018 Open House in Stuttgart Erleben Sie Grundlagenforschung hautnah!

Event 15-09-2018 Open House in Tübingen Come and visit our labs and learn about our research! Claudia Daefler Julia Braun Johannes Steinle

Event 14-09-2018 Max Planck Day in Tübingen Symposium "AI and society" - Science Slam - Light Installation - Get-together on the Max Planck Campus in Tübingen Claudia Daefler Johannes Steinle Julia Braun

Event 14-09-2018 Science Slam on the Max Planck Day in Stuttgart Wir feiern den Max-Planck-Tag am 14. September 2018 mit einem Science Slam für Schüler (ab Klasse 9) und ihre Lehrer. Dort können sie spannende Grundlagenforschung LIVE auf der Bühne erleben!

Event 14-09-2018 Symposium Artificial Intelligence and Society Max-Planck-Tag 2018</spam> The <a href="https://is.mpg.de/en/pages/ki-symposium-videos">accompanying videos</a> for the Symposium Artificial Intelligence and Society have been compiled on an <a href="https://is.mpg.de/en/pages/ki-symposium-videos">extra page.</a> Julia Braun Claudia Daefler Bernhard Schölkopf

Perceiving Systems Talk Richard Szeliski 07-09-2018 Visual Reconstruction and Image-Based Rendering The reconstruction of 3D scenes and their appearance from imagery is one of the longest-standing problems in computer vision. Originally developed to support robotics and artificial intelligence applications, it has found some of its most widespread use in support of interactive 3D scene visualization. One of the keys to this success has been the melding of 3D geometric and photometric reconstruction with a heavy re-use of the original imagery, which produces more realistic rendering than a pure 3D model-driven approach. In this talk, I give a retrospective of two decades of research in ... Mohamed Hassan

Perceiving Systems Talk Jim Mainprice 27-07-2018 Imitation of Human Motion Planning Humans act upon their environment through motion, the ability to plan their movements is therefore an essential component of their autonomy. In recent decades, motion planning has been widely studied in robotics and computer graphics. Nevertheless robots still fail to achieve human reactivity and coordination. The need for more efficient motion planning algorithms has been present through out my own research on "human-aware" motion planning, which aims to take the surroundings humans explicitly into account. I believe imitation learning is the key to this particular problem as it allows to ...

Perceiving Systems Talk Daniel Scharstein 24-07-2018 New Ideas for Stereo Matching of Untextured Scenes Two talks for the price of one! I will present my recent work on the challenging problem of stereo matching of scenes with little or no surface texture, attacking the problem from two very different angles. First, I will discuss how surface orientation priors can be added to the popular semi-global matching (SGM) algorithm, which significantly reduces errors on slanted weakly-textured surfaces. The orientation priors serve as a soft constraint during matching and can be derived in a variety of ways, including from low-resolution matching results and from monocular analysis and Manhatta... Anurag Ranjan

Theory of Inhomogeneous Condensed Matter Event 17-07-2018 Mauro Chinappi, University of Rome Tor Vergata, Italy Siegfried Dietrich

Perceiving Systems Talk Rıza Alp Güler 16-07-2018 DensePose: Dense Human Pose Estimation In The Wild Non-planar object deformations result in challenging but informative signal variations. We aim to recover this information in a feedforward manner by employing discriminatively trained convolutional networks. We formulate the task as a regression problem and train our networks by leveraging upon manually annotated correspondences between images and 3D surfaces. In this talk, the focus will be on our recent work "DensePose", where we form the "COCO-DensePose" dataset by introducing an efficient annotation pipeline to collect correspondences between 50K persons appearing in the COCO dataset a... Georgios Pavlakos

Theory of Inhomogeneous Condensed Matter Event 16-07-2018 Sayan Das, Indian Institute of Technology, Kharagpur, India Siegfried Dietrich

Talk Dr. Martin Hägele 13-07-2018 Household Assistants: the Path from the Care-o-bot Vision to First Products In 1995 Fraunhofer IPA embarked on a mission towards designing a personal robot assistant for everyday tasks. In the following years Care-O-bot developed into a long-term experiment for exploring and demonstrating new robot technologies and future product visions. The recent fourth generation of the Care-O-bot, introduced in 2014 aimed at designing an integrated system which addressed a number of innovations such as modularity, “low-cost” by making use of new manufacturing processes, and advanced human-user interaction. Some 15 systems were built and the intellectual property (IP) generated... Katherine J. Kuchenbecker Ildikó Papp-Wiedmann Matthias Tröndle Claudia Daefler

Talk Prof. Dr. Thomas Ertl 13-07-2018 Interactive Visualization – A Key Discipline for Big Data Analysis Big Data has become the general term relating to the benefits and threats which result from the huge amount of data collected in all parts of society. While data acquisition, storage and access are relevant technical aspects, the analysis of the collected data turns out to be at the core of the Big Data challenge. Automatic data mining and information retrieval techniques have made much progress but many application scenarios remain in which the human in the loop plays an essential role. Consequently, interactive visualization techniques have become a key discipline of Big Data analysis and... Katherine J. Kuchenbecker Ildikó Papp-Wiedmann Matthias Tröndle Claudia Daefler

Talk Dr. Sebastian Trimpe 13-07-2018 Learning Control for Intelligent Physical Systems Modern technology allows us to collect, process, and share more data than ever before. This data revolution opens up new ways to design control and learning algorithms, which will form the algorithmic foundation for future intelligent systems that shall act autonomously in the physical world. Starting from a discussion of the special challenges when combining machine learning and control, I will present some of our recent research in this exciting area. Using the example of the Apollo robot learning to balance a stick in its hand, I will explain how intelligent agents can learn new behav... Katherine J. Kuchenbecker Ildikó Papp-Wiedmann Matthias Tröndle Claudia Daefler

Talk Dr. Wenqi Hu 13-07-2018 Smart Magnetic Soft Material and its Application in Miniature Robot Katherine J. Kuchenbecker Ildikó Papp-Wiedmann Matthias Tröndle Claudia Daefler

Event 13-07-2018 Summer Colloquium 2018 MPI-IS cordially invites you to attend the 2018 Intelligent Systems Summer Colloquium Katherine J. Kuchenbecker Matthias Tröndle Ildikó Papp-Wiedmann Claudia Daefler

Talk Prof. Dr. Dawn Bonnell 13-07-2018 The Critical Role of Atoms at Surfaces and Interfaces: Do we really have control? Can we? With the ubiquity of catalyzed reactions in manufacturing, the emergence of the device laden internet of things, and global challenges with respect to water and energy, it has never been more important to understand atomic interactions in the functional materials that can provide solutions in these spaces. Katherine J. Kuchenbecker Ildikó Papp-Wiedmann Matthias Tröndle Claudia Daefler

Talk Carl E. Rasmussen 13-07-2018 Variational Inference, GPs and non-linear state space models Gaussian Processes are a principled, practical, probabilistic approach to learning in flexible non-parametric models and have found numerous applications in regression, classification, unsupervised learning and reinforcement learning. Inference, learning and prediction can be done exactly on small data sets with Gaussian likelihood. In more realistic application with large scale data and more complicated likelihoods approximations are necessary. The variational framework for approximate inference in Gaussian processes has emerged recently as a highly effective and practical tool. I will rev... Philipp Hennig

Micro, Nano, and Molecular Systems Talk Weiqiang Chen Ph.D. 12-07-2018 Microengineered Biosystems for Cancer: From Biology to Mechanics Taking advantages of state-of-art micro/nanotechnologies, fascinating functional biomaterials and integrated biosystems, we can address numerous important problems in fundamental biology as well as clinical applications in cancer diagnosis and treatment. Peer Fischer

Dynamic Locomotion Talk Robin Thandiackal 09-07-2018 Robin Thandiackal: Modeling anguilliform swimming, robotic swimming Exciting talk on modeling anguilliform swimming, robotic testing. Steve Heim Alexander Badri-Spröwitz

Autonomous Vision Talk Zeynep Akata 06-07-2018 Representing and Explaining Novel Concepts With Minimal Supervision Clearly explaining a rationale for a classification decision to an end-user can be as important as the decision itself. Existing approaches for deep visual recognition are generally opaque and do not output any justification text; contemporary vision-language models can describe image content but fail to take into account class-discriminative image aspects which justify visual predictions. In this talk, I will present my past and current work on Zero-Shot Learning, Vision and Language for Generative Modeling and Explainable Artificial Intelligence in that (1) how we can generalize the image... Andreas Geiger

Perceiving Systems Talk Elena Balashova (Sizikova) 03-07-2018 Structure-Aware Shape Synthesis Complex shapes can can be summarized using a coarsely defined structure which is consistent and robust across variety of observations. However, existing synthesis techniques do not consider structural decomposition during synthesis, causing generation of implausible or structurally unrealistic shapes. We explore how structure-aware reasoning can benefit existing generative techniques for complex 2D and 3D shapes. We evaluate our methodology on a 3D dataset of chairs and a 2D dataset of typefaces. Sergi Pujades

Haptic Intelligence IS Colloquium Prof. Dr. Cornelius Schwarz 02-07-2018 The Computational Skin. Tactile Perception based on Slip Movements. Touch requires mechanical contact and is governed by the physics of friction. Frictional movements may convert the continuous 3D profile of textural objects into discrete and probabilistic movement events of the viscoelastic integument (skin/hair) called stick-slip movements (slips). This complex transformation may further be determined by the microanatomy and the active movements of the sensing organ. Thus, the integument may realize a computation, transforming the tactile world in a context dependent way - long before it even activates neurons. The possibility that the tactile world is pe... Katherine J. Kuchenbecker

Autonomous Learning Talk Prof. William W. Hager 28-06-2018 Discrete approximations in optimal control: From Runge Kutta to Pseudospectral Methods Optimal control problems are often too complex to solve analytically. Computational methods usually replace the continuous infinite dimensional problem by a finite dimensional discrete approximation. The talk will survey classical discretization techniques based on a Runge-Kutta approximation to the differential equations (an h-method) and then introduce recent approximations based on collocation at the roots of orthogonal polynomials (a p-method). The best approximations are often achieved using an hp-framework that combines the best features of both approaches. Numerical results using t... Jia-Jie Zhu

IS Colloquium Borja de Balle Pigem 27-06-2018 Improving the Gaussian Mechanism for Differential Privacy The Gaussian mechanism is an essential building block used in multitude of differentially private data analysis algorithms. In this talk I will revisit the classical analysis of the Gaussian mechanism and show it has several important limitations. For example, our analysis reveals that the variance formula for the original mechanism is far from tight in the high privacy regime and that it cannot be extended to the low privacy regime. We address these limitations by developing a new Gaussian mechanism whose variance is optimally calibrated by solving an equation involving the Gaussian cumula... Michel Besserve Isabel Valera

Dynamic Locomotion Talk Daniel Häufle 23-06-2018 Daniel Häufle: Muscle dynamics and human movement Alexander Badri-Spröwitz

Haptic Intelligence IS Colloquium Yon Visell, PhD 20-06-2018 Haptic Engineering and Science at Multiple Scales I will describe recent research in my lab on haptics and robotics. It has been a longstanding challenge to realize engineering systems that can match the amazing perceptual and motor feats of biological systems for touch, including the human hand. Some of the difficulties of meeting this objective can be traced to our limited understanding of the mechanics, and to the high dimensionality of the signals, and to the multiple length and time scales - physical regimes - involved. An additional source of richness and complication arises from the sensitive dependence of what we feel on what ... Katherine J. Kuchenbecker

Talk Prof. Dr. Matthias Bethge 18-06-2018 Less-artificial intelligence

Probabilistic Numerics Talk Adrián Javaloy 15-06-2018 An approach to the text normalization problem making use of deep learning techniques The problem of text normalization is simple to understand: transform a given arbitrary text into its spoken form. In the context of text-to-speech systems – that we will focus on – this can be exemplified by turning the text “$200” into “two hundred dollars”. Lately, the interest of solving this problem with deep learning techniques has raised since it is a highly context-dependent problem that is still being solved by ad-hoc solutions. So much so that Google even started a contest in the web Kaggle to solve this problem. In this talk we will see how this problem has been approached as p... Philipp Hennig

Statistical Learning Theory Talk Karl Rohe 15-06-2018 Understanding Regularized Spectral Clustering via Graph Conductance This paper uses the relationship between graph conductance and spectral clustering to study (i) the failures of spectral clustering and (ii) the benefits of regularization. The explanation is simple. Sparse and stochastic graphs create a lot of small trees that are connected to the core of the graph by only one edge. Graph conductance is sensitive to these noisy "dangling sets." Spectral clustering inherits this sensitivity. The second part of the paper starts from a previously proposed form of regularized spectral clustering and shows that it is related to the graph conductance on a "regul... Damien Garreau

Perceiving Systems Talk Prof. Andrew Blake 14-06-2018 Quantifying the risk of collision for self driving cars Ahmed Osman

Haptic Intelligence Workshop 13-06-2018 From Fingertip Mechanics to Tactile Sensation It is well known that the dynamics of the interacting finger mediate the human tactile sensation of materials and textures but its contact dynamics also contribute to other aspects of human cognition such as proprioceptive perception and our capacity to dexterously manipulate objects. The broad range of perceptual phenomena stemming from finger mechanics makes it essential to develop further our understanding of the finger behavior during interaction and its perceptual consequences. David Gueorguiev

Talk Prof. Martin Spindler 11-06-2018 Double Machine Learning with two Applications: Transformation Models and Gaussian Graphical Models in High-Dimensional Settings In this talk first an introduction to the double machine learning framework is given. This allows inference on parameters in high-dimensional settings. Then, two applications are given, namely transformation models and Gaussian graphical models in high-dimensional settings. Both kind of models are widely used by practitioners. As high-dimensional data sets become more and more available, it is important to allow situations where the number of parameters is large compared to the sample size.

Empirical Inference Talk Prof. Martin Spindler 11-06-2018 Double Machine Learning with two Applications: Transformation Models and Gaussian Graphical Models in High-Dimensional Settings In this talk first an introduction to the double machine learning framework is given. This allows inference on parameters in high-dimensional settings. Then, two applications are given, namely transformation models and Gaussian graphical models in high-dimensional settings. Both kind of models are widely used by practitioners. As high-dimensional data sets become more and more available, it is important to allow situations where the number of parameters is large compared to the sample size. Philipp Geiger

Empirical Inference IS Colloquium Cédric Archambeau 11-06-2018 Learning Representations for Hyperparameter Transfer Learning Bayesian optimization (BO) is a model-based approach for gradient-free black-box function optimization, such as hyperparameter optimization. Typically, BO relies on conventional Gaussian process regression, whose algorithmic complexity is cubic in the number of evaluations. As a result, Gaussian process-based BO cannot leverage large numbers of past function evaluations, for example, to warm-start related BO runs. After a brief intro to BO and an overview of several use cases at Amazon, I will discuss a multi-task adaptive Bayesian linear regression model, whose computational complexity is ... Isabel Valera

Physical Intelligence Talk Dr. Greg Byrnes 08-06-2018 Biomechanical insights into flexible wings from gliding mammals Gliding evolved at least nine times in mammals. Despite the abundance and diversity of gliding mammals, little is known about their convergent morphology and mechanisms of aerodynamic control. Many gliding animals are capable of impressive and agile aerial behaviors and their flight performance depends on the aerodynamic forces resulting from airflow interacting with a flexible, membranous wing (patagium). Although the mechanisms that gliders use to control dynamic flight are poorly understood, the shape of the gliding membrane (e.g., angle of attack, camber) is likely a primary factor gove... Metin Sitti Ardian Jusufi

Perceiving Systems IS Colloquium Prof. Javier Cudeiro 08-06-2018 Lessons from the visual system to understand (and help) the brain Visual perception involves a complex interaction between feedforward and feedback processes. A mechanistic understanding of these processing, and its limitations, is a necessary first step towards elucidating key aspects of perceptual functions and dysfunctions. In this talk, I will review our ongoing effort towards the understanding of how feedback visual processing operates at the level of the thalamus, a dynamic relay station halfway between the retina and the cortex. I will present experimental evidence from several recent electrophysiology studies performed on subjects engaged in ... Daniel Cudeiro

Talk Dr. Hadi Eghlidi 07-06-2018 Single Entity Resolution Valving of Nanoscopic Species in Liquids Investigations and control of biological and synthetic nanoscopic species in liquids at the ultimate resolution of single entity, are important in diverse fields such as biology, medicine, physics, chemistry and emerging field of nanorobotics. Progress made to date on trapping and/or manipulating nanoscopic objects includes methods that use permanently imposed force fields of various kinds, such as optical, electrical and magnetic forces, to counteract their inherent Brownian motion. Peer Fischer Ardian Jusufi

Haptic Intelligence Talk Wenzhen Yuan 05-06-2018 Making Sense of the Physical World with High-Resolution Tactile Sensing Why cannot the current robots act intelligently in the real-world environment? A major challenge lies in the lack of adequate tactile sensing technologies. Robots need tactile sensing to understand the physical environment, and detect the contact states during manipulation. Progress requires advances in the sensing hardware, but also advances in the software that can exploit the tactile signals. We developed a high-resolution tactile sensor, GelSight, which measures the geometry and traction field of the contact surface. For interpreting the high-resolution tactile signal, we utilize both t... Katherine J. Kuchenbecker

Empirical Inference IS Colloquium Thomas Schön 28-05-2018 Learning dynamical systems using SMC Abstract: Sequential Monte Carlo (SMC) methods (including the particle filters and smoothers) allows us to compute probabilistic representations of the unknown objects in models used to represent for example nonlinear dynamical systems. This talk has three connected parts: 1. A (hopefully pedagogical) introduction to probabilistic modelling of dynamical systems and an explanation of the SMC method. 2. In learning unknown parameters appearing in nonlinear state-space models using maximum likelihood it is natural to make use of SMC to compute unbiased estimates of the intractable likelihood.... Philipp Hennig

Haptic Intelligence IS Colloquium Karon MacLean 28-05-2018 Making Haptics and its Design Accessible Today’s advances in tactile sensing and wearable, IOT and context-aware computing are spurring new ideas about how to configure touch-centered interactions in terms of roles and utility, which in turn expose new technical and social design questions. But while haptic actuation, sensing and control are improving, incorporating them into a real-world design process is challenging and poses a major obstacle to adoption into everyday technology. Some classes of haptic devices, e.g., grounded force feedback, remain expensive and limited in range. I’ll describe some recent highlights of an o... Katherine J. Kuchenbecker

Perceiving Systems IS Colloquium Thabo Beeler 25-05-2018 Digital Humans At Disney Research Disney Research has been actively pushing the state-of-the-art in digitizing humans over the past decade, impacting both academia and industry. In this talk I will give an overview of a selected few projects in this area, from research into production. I will be talking about photogrammetric shape acquisition and dense performance capture for faces, eye and teeth scanning and parameterization, as well as physically based capture and modelling for hair and volumetric tissues. Timo Bolkart

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