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2024


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Interpreting How Large Language Models Handle Facts and Counterfactuals through Mechanistic Interpretability

Ortu, F.

University of Trieste, Italy, March 2024 (mastersthesis)

ei

[BibTex]

2023


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Denoising Representation Learning for Causal Discovery

Sakenyte, U.

Université de Genèva, Switzerland, December 2023, external supervision (mastersthesis)

ei

[BibTex]

2023


[BibTex]


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Efficient Sampling from Differentiable Matrix Elements

Kofler, A.

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

ei

[BibTex]

[BibTex]


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Intrinsic complexity and mechanisms of expressivity of cortical neurons

Spieler, A. M.

University of Tübingen, Germany, March 2023 (mastersthesis)

ei

[BibTex]

[BibTex]


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CausalEffect Estimation by Combining Observational and Interventional Data

Kladny, K.

ETH Zurich, Switzerland, February 2023 (mastersthesis)

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[BibTex]

[BibTex]


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Towards Generative Machine Teaching

Qui, Z.

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

ei

[BibTex]

[BibTex]


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ArchiSound: Audio Generation with Diffusion

Schneider, F.

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

ei

[BibTex]

[BibTex]


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Generation and Quantification of Spin in Robot Table Tennis

Dittrich, A.

University of Stuttgart, Germany, January 2023 (mastersthesis)

ei

[BibTex]

[BibTex]


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Natural Language Processing for Policymaking

Jin, Z., Mihalcea, R.

In Handbook of Computational Social Science for Policy, pages: 141-162, 7, (Editors: Bertoni, E. and Fontana, M. and Gabrielli, L. and Signorelli, S. and Vespe, M.), Springer International Publishing, 2023 (inbook)

ei

DOI [BibTex]

DOI [BibTex]

2022


Magnetic Micro-/Nanopropellers  for Biomedicine
Magnetic Micro-/Nanopropellers for Biomedicine

Qiu, T., Jeong, M., Goyal, R., Kadiri, V., Sachs, J., Fischer, P.

In Field-Driven Micro and Nanorobots for Biology and Medicine, pages: 389-410, 16, (Editors: Sun, Y. and Wang, X. and Yu, J.), Springer, Cham, 2022 (inbook)

Abstract
In nature, many bacteria swim by rotating their helical flagella. A particularly promising class of artificial micro- and nano-robots mimic this propeller-like propulsion mechanism to move through fluids and tissues for applications in minimally-invasive medicine. Several fundamental challenges have to be overcome in order to build micro-machines that move similar to bacteria for in vivo applications. Here, we review recent advances of magnetically-powered micro-/nano-propellers. Four important aspects of the propellers – the geometrical shape, the fabrication method, the generation of magnetic fields for actuation, and the choice of biocompatible magnetic materials – are highlighted. First, the fundamental requirements are elucidated that arise due to hydrodynamics at low Reynolds (Re) number. We discuss the role that the propellers’ shape and symmetry play in realizing effective propulsion at low Re. Second, the additive nano-fabrication method Glancing Angle Deposition is discussed as a versatile technique to quickly grow large numbers of designer nano-helices. Third, systems to generate rotating magnetic fields via permanent magnets or electromagnetic coils are presented. And finally, the biocompatibility of the magnetic materials is discussed. Iron-platinum is highlighted due to its biocompatibility and its superior magnetic properties, which is promising for targeted delivery, minimally-invasive magnetic nano-devices and biomedical applications.

pf

link (url) DOI [BibTex]

2022


link (url) DOI [BibTex]


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Life Improvement Science

Lieder, F., Prentice, M.

In Encyclopedia of Quality of Life and Well-Being Research, Springer, November 2022 (inbook)

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DOI [BibTex]

DOI [BibTex]


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Investigating Independent Mechanisms in Neural Networks

Liang, W.

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

ei

[BibTex]

[BibTex]


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Causality, causal digital twins, and their applications

Schölkopf, B.

Machine Learning for Science: Bridging Data-Driven and Mechanistic Modelling (Dagstuhl Seminar 22382), (Editors: Berens, Philipp and Cranmer, Kyle and Lawrence, Neil D. and von Luxburg, Ulrike and Montgomery, Jessica), September 2022 (talk)

ei

link (url) DOI [BibTex]

link (url) DOI [BibTex]


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

Feil, M.

Technnical University Munich, Germany, September 2022 (mastersthesis)

ei

[BibTex]

[BibTex]


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Independent Mechanism Analysis for High Dimensions

Sliwa, J.

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

ei

[BibTex]

[BibTex]


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On the Adversarial Robustness of Causal Algorithmic Recourse

Dominguez-Olmedo, R.

University of Tübingen, Germany, August 2022 (mastersthesis)

ei

[BibTex]

[BibTex]


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Independent Mechanism Analysis in High-Dimensional Observation Spaces

Ghosh, S.

ETH Zurich, Switzerland, June 2022 (mastersthesis)

ei

[BibTex]

[BibTex]


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Causal Models for Dynamical Systems

Peters, J., Bauer, S., Pfister, N.

In Probabilistic and Causal Inference: The Works of Judea Pearl, pages: 671-690, 1, Association for Computing Machinery, 2022 (inbook)

ei

arXiv DOI [BibTex]

arXiv DOI [BibTex]


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Towards Causal Algorithmic Recourse

Karimi, A. H., von Kügelgen, J., Schölkopf, B., Valera, I.

In xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers, pages: 139-166, (Editors: Holzinger, Andreas and Goebel, Randy and Fong, Ruth and Moon, Taesup and Müller, Klaus-Robert and Samek, Wojciech), Springer International Publishing, 2022 (inbook)

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DOI [BibTex]

DOI [BibTex]


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CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations

Salewski, L., Koepke, A. S., Lensch, H. P. A., Akata, Z.

In xxAI - Beyond Explainable AI: International Workshop, Held in Conjunction with ICML 2020, July 18, 2020, Vienna, Austria, Revised and Extended Papers, pages: 69-88, (Editors: Holzinger, Andreas and Goebel, Randy and Fong, Ruth and Moon, Taesup and Müller, Klaus-Robert and Samek, Wojciech), Springer International Publishing, 2022 (inbook)

ei

DOI [BibTex]

DOI [BibTex]


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Causality for Machine Learning

Schölkopf, B.

In Probabilistic and Causal Inference: The Works of Judea Pearl, pages: 765-804, 1, Association for Computing Machinery, New York, NY, USA, 2022 (inbook)

ei

arXiv DOI [BibTex]

arXiv DOI [BibTex]


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Voltage dependent investigations on the spin polarization of layered heterostructues

Miller, M.

Universität Stuttgart, Stuttgart, 2022 (mastersthesis)

mms

[BibTex]

[BibTex]

2021


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Learning Neural Causal Models with Active Interventions

Scherrer, N.

ETH Zurich, Switzerland, November 2021 (mastersthesis)

ei

[BibTex]

2021


[BibTex]


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Study of the Interventional Consistency of Autoencoders

Lanzillotta, G.

ETH Zurich, Switzerland, October 2021 (mastersthesis)

ei

[BibTex]

[BibTex]


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Physically Plausible Tracking & Reconstruction of Dynamic Objects

Strecke, M., Stückler, J.

KIT Science Week Scientific Conference & DGR-Days 2021, October 2021 (talk)

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[BibTex]

[BibTex]


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Electriflow: Augmenting Books With Tangible Animation Using Soft Electrohydraulic Actuators

Purnendu, , Novack, S., Acome, E., Alistar, M., Keplinger, C., Gross, M. D., Bruns, C., Leithinger, D.

In ACM SIGGRAPH 2021 Labs, pages: 1-2, Association for Computing Machinery, SIGGRAPH 2021, August 2021 (inbook)

Abstract
We present Electriflow: a method of augmenting books with tangible animation employing soft electrohydraulic actuators. These actuators are compact, silent and fast in operation, and can be fabricated with commodity materials. They generate an immediate hydraulic force upon electrostatic activation without an external fluid supply source, enabling a simple and self-contained design. Electriflow actuators produce an immediate shape transition from flat to folded state which enabled their seamless integration into books. For the Emerging Technologies exhibit, we will demonstrate the prototype of a book augmented with the capability of tangible animation.

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Supplemental Material link (url) DOI [BibTex]

Supplemental Material link (url) DOI [BibTex]


Improving Human Decision-Making by Discovering Efficient Strategies for Hierarchical Planning
Improving Human Decision-Making by Discovering Efficient Strategies for Hierarchical Planning

Heindrich, L., Consul, S., Stojcheski, J., Lieder, F.

Tübingen, Germany, The first edition of Life Improvement Science Conference, June 2021 (talk) Accepted

Abstract
The discovery of decision strategies is an essential part of creating effective cognitive tutors that teach planning and decision-making skills to humans. In the context of bounded rationality, this requires weighing the benefits of different planning operations compared to their computational costs. For small decision problems, it has already been shown that near-optimal decision strategies can be discovered automatically and that the discovered strategies can be taught to humans to increase their performance. Unfortunately, these near-optimal strategy discovery algorithms have not been able to scale well to larger problems due to their computational complexity. In this talk, we will present recent work at the Rationality Enhancement Group to overcome the computational bottleneck of existing strategy discovery algorithms. Our approach makes use of the hierarchical structure of human behavior by decomposing sequential decision problems into two sub-problems: setting a goal and planning how to achieve it. An additional metacontroller component is introduced to switch the current goal when it becomes beneficial. The hierarchical decomposition enables us to discover near-optimal strategies for human planning in larger and more complex tasks than previously possible. We then show in online experiments that teaching the discovered strategies to humans improves their performance in complex sequential decision-making tasks.

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Project Page [BibTex]

Project Page [BibTex]


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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)

hi

[BibTex]

[BibTex]


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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)

mms

[BibTex]


Scientific Report 2016 - 2021
Scientific Report 2016 - 2021
2021 (mpi_year_book)

Abstract
This report presents research done at the Max Planck Institute for Intelligent Systems from January2016 to November 2021. It is our fourth report since the founding of the institute in 2011. Dueto the fact that the upcoming evaluation is an extended one, the report covers a longer reportingperiod.This scientific report is organized as follows: we begin with an overview of the institute, includingan outline of its structure, an introduction of our latest research departments, and a presentationof our main collaborative initiatives and activities (Chapter1). The central part of the scientificreport consists of chapters on the research conducted by the institute’s departments (Chapters2to6) and its independent research groups (Chapters7 to24), as well as the work of the institute’scentral scientific facilities (Chapter25). For entities founded after January 2016, the respectivereport sections cover work done from the date of the establishment of the department, group, orfacility. These chapters are followed by a summary of selected outreach activities and scientificevents hosted by the institute (Chapter26). The scientific publications of the featured departmentsand research groups published during the 6-year review period complete this scientific report.

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Scientific Report 2016 - 2021 [BibTex]

2020


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Hydromagnonics: Manipulation of magnonic systems with hydrogen

Sauter, R.

Universität Stuttgart, Stuttgart, December 2020 (mastersthesis)

mms

[BibTex]

2020


[BibTex]


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A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning

Ahmed, O.

ETH Zurich, Switzerland, October 2020 (mastersthesis)

ei

[BibTex]

[BibTex]


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Deep learning for the parameter estimation of tight-binding Hamiltonians

Cacioppo, A.

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

ei

[BibTex]

[BibTex]


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Learning Algorithms, Invariances, and the Real World

Zecevic, M.

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

ei

[BibTex]

[BibTex]


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Interaction of hydrogen isotopes with flexible metal-organic frameworks

Bondorf, L.

Universität Stuttgart, Stuttgart, February 2020 (mastersthesis)

mms

[BibTex]

[BibTex]


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Developing new methods for routing and optimal transport on networks

Lonardi, A.

Università degli studi di Padova, 2020 (mastersthesis)

pio

pdf [BibTex]

pdf [BibTex]


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TUM Flyers: Vision-Based MAV Navigation for Systematic Inspection of Structures

Usenko, V., Stumberg, L. V., Stückler, J., Cremers, D.

In Bringing Innovative Robotic Technologies from Research Labs to Industrial End-users: The Experience of the European Robotics Challenges, 136, pages: 189-209, Springer Tracts in Advanced Robotics, Springer International Publishing, 2020 (inbook)

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link (url) DOI [BibTex]

link (url) DOI [BibTex]


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Edge-Disjoint Path Problem on Stochastic Block Models through Message Passing

Lorenzo Ferretti

Sapienza Università di Roma, 2020 (mastersthesis)

pio

[BibTex]

[BibTex]


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Adopting the Boundary Homogenization Approximation from Chemical Kinetics to Motile Chemically Active Particles

Popescu, M. N., Uspal, W. E.

In Chemical Kinetics, pages: 517-540, (Editors: Lindenberg, Katja and Metzler, Ralf and Oshanin, Gleb), World Scientific, New Jersey, NJ, 2020 (incollection)

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DOI [BibTex]

DOI [BibTex]


Colloidal particles supporting urase activity
Colloidal particles supporting urase activity

Baldauf, A.

Univ. of Stuttgart, 2020 (mastersthesis)

pf

[BibTex]

[BibTex]


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Soft Microrobots Based on Photoresponsive Materials

Palagi, S.

In Mechanically Responsive Materials for Soft Robotics, pages: 327-362, (Editors: Koshima, Hideko), Wiley-VCH, Weinheim, 2020 (incollection)

pf

DOI [BibTex]

DOI [BibTex]


Diffusion studies on biomolecules by NMR
Diffusion studies on biomolecules by NMR

Bochert, I.

Univ. of Stuttgart, 2020 (mastersthesis)

pf

[BibTex]

[BibTex]

2019


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Multivariate coupling estimation between continuous signals and point processes

Safavi, S., Logothetis, N., Besserve, M.

Neural Information Processing Systems 2019 - Workshop on Learning with Temporal Point Processes, December 2019 (talk)

ei

Talk video link (url) [BibTex]

2019


Talk video link (url) [BibTex]