Publications | Max Planck Institute for Intelligent Systems

ei Sakenyte, U. Denoising Representation Learning for Causal Discovery Université de Genèva, Switzerland, December 2023, external supervision (mastersthesis)

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Efficient Sampling from Differentiable Matrix Elements

Kofler, A.

Technical University of Munich, Germany, September 2023 (mastersthesis)

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ei Kofler, A. Efficient Sampling from Differentiable Matrix Elements Technical University of Munich, Germany, September 2023 (mastersthesis)

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Intrinsic complexity and mechanisms of expressivity of cortical neurons

Spieler, A. M.

University of Tübingen, Germany, March 2023 (mastersthesis)

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ei Spieler, A. M. Intrinsic complexity and mechanisms of expressivity of cortical neurons University of Tübingen, Germany, March 2023 (mastersthesis)

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CausalEffect Estimation by Combining Observational and Interventional Data

Kladny, K.

ETH Zurich, Switzerland, February 2023 (mastersthesis)

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lds ei Kladny, K. CausalEffect Estimation by Combining Observational and Interventional Data ETH Zurich, Switzerland, February 2023 (mastersthesis)

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Towards Generative Machine Teaching

Qui, Z.

Technical University of Munich, Germany, February 2023 (mastersthesis)

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ei Qui, Z. Towards Generative Machine Teaching Technical University of Munich, Germany, February 2023 (mastersthesis)

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ArchiSound: Audio Generation with Diffusion

Schneider, F.

ETH Zurich, Switzerland, January 2023, external supervision (mastersthesis)

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ei Schneider, F. ArchiSound: Audio Generation with Diffusion ETH Zurich, Switzerland, January 2023, external supervision (mastersthesis)

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Generation and Quantification of Spin in Robot Table Tennis

Dittrich, A.

University of Stuttgart, Germany, January 2023 (mastersthesis)

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ei Dittrich, A. Generation and Quantification of Spin in Robot Table Tennis University of Stuttgart, Germany, January 2023 (mastersthesis)

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An Open-Source Modular Treadmill for Dynamic Force Measurement with Load Dependant Range Adjustment

Sarvestani, A., Ruppert, F., Badri-Spröwitz, A.

2023 (unpublished) Submitted

Abstract

Ground reaction force sensing is one of the key components of gait analysis in legged locomotion research. To measure continuous force data during locomotion, we present a novel compound instrumented treadmill design. The treadmill is 1.7 m long, with a natural frequency of 170 Hz and an adjustable range that can be used for humans and small robots alike. Here, we present the treadmill’s design methodology and characterize it in its natural frequency, noise behavior and real-life performance. Additionally, we apply an ISO 376 norm conform calibration procedure for all spatial force directions and center of pressure position. We achieve a force accuracy of ≤ 5.6 N for the ground reaction forces and ≤ 13 mm in center of pressure position.

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arXiv link (url) DOI [BibTex]

dlg Sarvestani, A., Ruppert, F., Badri-Spröwitz, A. An Open-Source Modular Treadmill for Dynamic Force Measurement with Load Dependant Range Adjustment 2023 (unpublished) Submitted

arXiv link (url) DOI [BibTex]

2022

Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI)

Biester, L., Demszky, D., Jin, Z., Sachan, M., Tetreault, J., Wilson, S., Xiao, L., Zhao, J.

Association for Computational Linguistics, December 2022 (proceedings)

link (url) [BibTex]

2022

ei Biester, L., Demszky, D., Jin, Z., Sachan, M., Tetreault, J., Wilson, S., Xiao, L., Zhao, J. Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI) Association for Computational Linguistics, December 2022 (proceedings)

link (url) [BibTex]

Investigating Independent Mechanisms in Neural Networks

Liang, W.

Université Paris-Saclay, France, October 2022 (mastersthesis)

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ei Liang, W. Investigating Independent Mechanisms in Neural Networks Université Paris-Saclay, France, October 2022 (mastersthesis)

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Modeling subgroup differences in fMRI data: disentangling subgroup-specific responses from shared ones

Keidar, D.

ETH Zurich, Switzerland, October 2022 (mastersthesis)

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ei Keidar, D. Modeling subgroup differences in fMRI data: disentangling subgroup-specific responses from shared ones ETH Zurich, Switzerland, October 2022 (mastersthesis)

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Multi-Target Multi-Object Manipulation using Relational Deep Reinforcement Learning

Feil, M.

Technnical University Munich, Germany, September 2022 (mastersthesis)

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ei Feil, M. Multi-Target Multi-Object Manipulation using Relational Deep Reinforcement Learning Technnical University Munich, Germany, September 2022 (mastersthesis)

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Independent Mechanism Analysis for High Dimensions

Sliwa, J.

University of Tübingen, Germany, September 2022, (Graduate Training Centre of Neuroscience) (mastersthesis)

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ei Sliwa, J. Independent Mechanism Analysis for High Dimensions University of Tübingen, Germany, September 2022, (Graduate Training Centre of Neuroscience) (mastersthesis)

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On the Adversarial Robustness of Causal Algorithmic Recourse

Dominguez-Olmedo, R.

University of Tübingen, Germany, August 2022 (mastersthesis)

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ei Dominguez-Olmedo, R. On the Adversarial Robustness of Causal Algorithmic Recourse University of Tübingen, Germany, August 2022 (mastersthesis)

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Independent Mechanism Analysis in High-Dimensional Observation Spaces

Ghosh, S.

ETH Zurich, Switzerland, June 2022 (mastersthesis)

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ei Ghosh, S. Independent Mechanism Analysis in High-Dimensional Observation Spaces ETH Zurich, Switzerland, June 2022 (mastersthesis)

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Proceedings of the First Conference on Causal Learning and Reasoning (CLeaR 2022)

Schölkopf, B., Uhler, C., Zhang, K.

177, Proceedings of Machine Learning Research, PMLR, April 2022 (proceedings)

link (url) [BibTex]

ei Schölkopf, B., Uhler, C., Zhang, K. Proceedings of the First Conference on Causal Learning and Reasoning (CLeaR 2022) 177, Proceedings of Machine Learning Research, PMLR, April 2022 (proceedings)

link (url) [BibTex]

Voltage dependent investigations on the spin polarization of layered heterostructues

Miller, M.

Universität Stuttgart, Stuttgart, 2022 (mastersthesis)

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mms Miller, M. Voltage dependent investigations on the spin polarization of layered heterostructues Universität Stuttgart, Stuttgart, 2022 (mastersthesis)

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2021

Learning Neural Causal Models with Active Interventions

Scherrer, N.

ETH Zurich, Switzerland, November 2021 (mastersthesis)

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2021

ei Scherrer, N. Learning Neural Causal Models with Active Interventions ETH Zurich, Switzerland, November 2021 (mastersthesis)

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HealthGen: Conditional Generation of Realistic Medical Time Series with Informative Missingness

Bing, S.

ETH Zurich, Switzerland, October 2021 (mastersthesis)

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ei Bing, S. HealthGen: Conditional Generation of Realistic Medical Time Series with Informative Missingness ETH Zurich, Switzerland, October 2021 (mastersthesis)

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Study of the Interventional Consistency of Autoencoders

Lanzillotta, G.

ETH Zurich, Switzerland, October 2021 (mastersthesis)

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ei Lanzillotta, G. Study of the Interventional Consistency of Autoencoders ETH Zurich, Switzerland, October 2021 (mastersthesis)

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Training with Few to Manipulate Many. On OOD generalization in relational reinforcement learning

Mambelli, D.

ETH Zurich, Switzerland, October 2021 (mastersthesis)

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ei Mambelli, D. Training with Few to Manipulate Many. On OOD generalization in relational reinforcement learning ETH Zurich, Switzerland, October 2021 (mastersthesis)

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Proceedings of the 1st Workshop on NLP for Positive Impact

Field, A., Prabhumoye, S., Sap, M., Jin, Z., Zhao, J., Brockett, C.

Association for Computational Linguistics, August 2021 (proceedings)

link (url) [BibTex]

ei Field, A., Prabhumoye, S., Sap, M., Jin, Z., Zhao, J., Brockett, C. Proceedings of the 1st Workshop on NLP for Positive Impact Association for Computational Linguistics, August 2021 (proceedings)

link (url) [BibTex]

Promoting metacognitive learning through systematic reflection

Frederic Becker, , Lieder, F.

The first edition of Life Improvement Science Conference, June 2021 (poster)

Abstract

Human decision-making is sometimes systematically biased toward suboptimal decisions. For example, people often make short-sighted choices because they don't give enough weight to the long-term consequences of their actions. Previous studies showed that it is possible to overcome such biases by teaching people a more rational decision strategy through instruction, demonstrations, or practice with feedback. The benefits of these approaches tend to be limited to situations that are very similar to those used during the training. One way to overcome this limitation is to create general tools and strategies that people can use to improve their decision-making in any situation. Here we propose one such approach, namely directing people to systematically reflect on how they make their decisions. In systematic reflection, past experience is re-evaluated with the intention to learn. In this study, we investigate how reflection affects how people learn to plan and whether reflective learning can help people to discover more far-sighted planning strategies. In our experiment participants solve a series of 30 planning problems where the immediate rewards are smaller and therefore less important than long-term rewards. Building on Wolfbauer et al. (2020), the experimental group is guided by four reflection prompts asking the participant to describe their planning strategy, the strategy's performance, and his or her emotional response, insights, and intention to change their strategy. The control group practices planning without reflection prompts. Our pilot data suggest that systematic reflection helps people to more rapidly discover adaptive planning strategies. Our findings suggest that reflection is useful not only for helping people learn what to do in a specific situation but also for helping people learn how to think about what to do. In future work, we will compare the effects of different types of reflection on the subsequent changes in people's decision strategies. Developing apps that prompt people to reflect on their decisions may be a promising approach to accelerating cognitive growth and promoting lifelong learning.

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re Frederic Becker, , Lieder, F. Promoting metacognitive learning through systematic reflection The first edition of Life Improvement Science Conference, June 2021 (poster)

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Robotic Surgery Training in AR: Multimodal Record and Replay

Krauthausen, F.

pages: 1-147, University of Stuttgart, Stuttgart, May 2021, Study Program in Software Engineering (mastersthesis)

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hi Krauthausen, F. Robotic Surgery Training in AR: Multimodal Record and Replay pages: 1-147, University of Stuttgart, Stuttgart, May 2021, Study Program in Software Engineering (mastersthesis)

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Direct detection of spin Hall effect induced torques in platinum/ferromagnetic bilayer systems

Alten, F.

Universität Stuttgart, Stuttgart, January 2021 (mastersthesis)

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mms Alten, F. Direct detection of spin Hall effect induced torques in platinum/ferromagnetic bilayer systems Universität Stuttgart, Stuttgart, January 2021 (mastersthesis)

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Community detection in heterogeneously attributed networks

Zottino, N.

Politecnico di Torino, 2021 (mastersthesis)

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link (url) [BibTex]

pio Zottino, N. Community detection in heterogeneously attributed networks Politecnico di Torino, 2021 (mastersthesis)

link (url) [BibTex]

2020

Voltage dependent interfacial magnetism in multilayer systems

Nacke, R.

Universität Stuttgart, Stuttgart, December 2020 (thesis)

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2020

mms Nacke, R. Voltage dependent interfacial magnetism in multilayer systems Universität Stuttgart, Stuttgart, December 2020 (thesis)

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Hydromagnonics: Manipulation of magnonic systems with hydrogen

Sauter, R.

Universität Stuttgart, Stuttgart, December 2020 (mastersthesis)

mms

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mms Sauter, R. Hydromagnonics: Manipulation of magnonic systems with hydrogen Universität Stuttgart, Stuttgart, December 2020 (mastersthesis)

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A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning

Ahmed, O.

ETH Zurich, Switzerland, October 2020 (mastersthesis)

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ei Ahmed, O. A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning ETH Zurich, Switzerland, October 2020 (mastersthesis)

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A Comprehensive Benchmark Evaluation of Synthetic Data Generation for Biomedical Imaging

DuMont Schütte, A.

ETH Zurich, Switzerland, October 2020 (mastersthesis)

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ei DuMont Schütte, A. A Comprehensive Benchmark Evaluation of Synthetic Data Generation for Biomedical Imaging ETH Zurich, Switzerland, October 2020 (mastersthesis)

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Towards Hybrid Active and Passive Compliant Mechanisms in Legged Robots

Milad Shafiee Ashtiani, A. A. S., Badri-Sproewitz, A.

IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, October 2020 (poster) Accepted

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Abstract Poster [BibTex]

dlg Milad Shafiee Ashtiani, A. A. S., Badri-Sproewitz, A. Towards Hybrid Active and Passive Compliant Mechanisms in Legged Robots IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS), IEEE, October 2020 (poster) Accepted

Abstract Poster [BibTex]

Deep learning for the parameter estimation of tight-binding Hamiltonians

Cacioppo, A.

University of Roma, La Sapienza, Italy, May 2020 (mastersthesis)

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ei Cacioppo, A. Deep learning for the parameter estimation of tight-binding Hamiltonians University of Roma, La Sapienza, Italy, May 2020 (mastersthesis)

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VP above or below? A new perspective on the story of the virtual point

Drama, Ö., Badri-Spröwitz, A.

Dynamic Walking, May 2020 (poster)

Abstract

The spring inverted pendulum model with an extended trunk (TSLIP) is widely used to investigate the postural stability in bipedal locomotion [1, 2]. The challenge of the model is to define a hip torque that generates feasible gait patterns while stabilizing the floating trunk. The virtual point (VP) method is proposed as a simplified solution, where the hip torque is coupled to the passive compliant leg force via a virtual point. This geometric coupling is based on the assumption that the instantaneous ground reaction forces of the stance phase (GRF) intersect at a single virtual point.

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Poster Abstract link (url) [BibTex]

dlg Drama, Ö., Badri-Spröwitz, A. VP above or below? A new perspective on the story of the virtual point Dynamic Walking, May 2020 (poster)

Poster Abstract link (url) [BibTex]

Viscous Damping in Legged Locomotion

Mo, A., Izzi, F., Haeufle, D. F. B., Badri-Spröwitz, A.

Dynamic Walking, May 2020 (poster)

Abstract

Damping likely plays an essential role in legged animal locomotion, but remains an insufficiently understood mechanism. Intrinsic damping muscle forces can potentially add to the joint torque output during unexpected impacts, stabilise movements, convert the system’s energy, and reject unexpected perturbations.

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Abstract Poster link (url) Project Page [BibTex]

dlg Mo, A., Izzi, F., Haeufle, D. F. B., Badri-Spröwitz, A. Viscous Damping in Legged Locomotion Dynamic Walking, May 2020 (poster)

Abstract Poster link (url) Project Page [BibTex]

How Quadrupeds Benefit from Lower Leg Passive Elasticity

Ruppert, F., Badri-Spröwitz, A.

Dynamic Walking, May 2020 (poster)

Abstract

Recently developed and fully actuated, legged robots start showing exciting locomotion capabilities, but rely heavily on high-power actuators, high-frequency sensors, and complex locomotion controllers. The engineering solutions implemented in these legged robots are much different compared to animals. Vertebrate animals share magnitudes slower neurocontrol signal velocities [1] compared to their robot counterparts. Also, animals feature a plethora of cascaded and underactuated passive elastic structures [2].

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Abstract Poster link (url) Project Page [BibTex]

dlg Ruppert, F., Badri-Spröwitz, A. How Quadrupeds Benefit from Lower Leg Passive Elasticity Dynamic Walking, May 2020 (poster)

Abstract Poster link (url) Project Page [BibTex]

Learning Algorithms, Invariances, and the Real World

Zecevic, M.

Technical University of Darmstadt, Germany, April 2020 (mastersthesis)

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ei Zecevic, M. Learning Algorithms, Invariances, and the Real World Technical University of Darmstadt, Germany, April 2020 (mastersthesis)

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Interaction of hydrogen isotopes with flexible metal-organic frameworks

Bondorf, L.

Universität Stuttgart, Stuttgart, February 2020 (mastersthesis)

mms

[BibTex]

mms Bondorf, L. Interaction of hydrogen isotopes with flexible metal-organic frameworks Universität Stuttgart, Stuttgart, February 2020 (mastersthesis)

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Potential for elastic soft tissue deformation and mechanosensory function within the lumbosacral spinal canal of birds

Kamska, V., Daley, M., Badri-Spröwitz, A.

Society for Integrative and Comparative Biology Annual Meeting (SICB Annual Meeting 2020), January 2020 (poster)

dlg

DOI [BibTex]

dlg Kamska, V., Daley, M., Badri-Spröwitz, A. Potential for elastic soft tissue deformation and mechanosensory function within the lumbosacral spinal canal of birds Society for Integrative and Comparative Biology Annual Meeting (SICB Annual Meeting 2020), January 2020 (poster)

DOI [BibTex]

25th International Symposium on Vision, Modeling and Visualization, VMV 2020

(Editors: Jens Krüger and Matthias Nießner and Jörg Stückler), Eurographics Association, 2020 (proceedings)

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ev 25th International Symposium on Vision, Modeling and Visualization, VMV 2020 (Editors: Jens Krüger and Matthias Nießner and Jörg Stückler), Eurographics Association, 2020 (proceedings)

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Excursion Search for Constrained Bayesian Optimization under a Limited Budget of Failures

Marco, A., Rohr, A. V., Baumann, D., Hernández-Lobato, J. M., Trimpe, S.

2020 (proceedings) In revision

Abstract

When learning to ride a bike, a child falls down a number of times before achieving the first success. As falling down usually has only mild consequences, it can be seen as a tolerable failure in exchange for a faster learning process, as it provides rich information about an undesired behavior. In the context of Bayesian optimization under unknown constraints (BOC), typical strategies for safe learning explore conservatively and avoid failures by all means. On the other side of the spectrum, non conservative BOC algorithms that allow failing may fail an unbounded number of times before reaching the optimum. In this work, we propose a novel decision maker grounded in control theory that controls the amount of risk we allow in the search as a function of a given budget of failures. Empirical validation shows that our algorithm uses the failures budget more efficiently in a variety of optimization experiments, and generally achieves lower regret, than state-of-the-art methods. In addition, we propose an original algorithm for unconstrained Bayesian optimization inspired by the notion of excursion sets in stochastic processes, upon which the failures-aware algorithm is built.

am ics

arXiv code (python) PDF [BibTex]