Publications | Empirical Inference - Max Planck Institute for Intelligent Systems

2023

Denoising Representation Learning for Causal Discovery

Sakenyte, U.

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

2023

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

Navigating the Ocean of Biases: Political Bias Attribution in Language Models via Causal Structures

Jenny, D.

ETH Zurich, Switzerland, November 2023, external supervision (thesis)

Jenny, D. Navigating the Ocean of Biases: Political Bias Attribution in Language Models via Causal Structures ETH Zurich, Switzerland, November 2023, external supervision (thesis)

Efficient Sampling from Differentiable Matrix Elements

Kofler, A.

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

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

Intrinsic complexity and mechanisms of expressivity of cortical neurons

Spieler, A. M.

University of Tübingen, Germany, March 2023 (mastersthesis)

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

CausalEffect Estimation by Combining Observational and Interventional Data

Kladny, K.

ETH Zurich, Switzerland, February 2023 (mastersthesis)

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

Towards Generative Machine Teaching

Qui, Z.

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

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

ArchiSound: Audio Generation with Diffusion

Schneider, F.

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

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

Generation and Quantification of Spin in Robot Table Tennis

Dittrich, A.

University of Stuttgart, Germany, January 2023 (mastersthesis)

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

2022

Investigating Independent Mechanisms in Neural Networks

Liang, W.

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

2022

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

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

Keidar, D.

ETH Zurich, Switzerland, October 2022 (mastersthesis)

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

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

Feil, M.

Technnical University Munich, Germany, September 2022 (mastersthesis)

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

Independent Mechanism Analysis for High Dimensions

Sliwa, J.

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

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

On the Adversarial Robustness of Causal Algorithmic Recourse

Dominguez-Olmedo, R.

University of Tübingen, Germany, August 2022 (mastersthesis)

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

Independent Mechanism Analysis in High-Dimensional Observation Spaces

Ghosh, S.

ETH Zurich, Switzerland, June 2022 (mastersthesis)

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

2021

Learning Neural Causal Models with Active Interventions

Scherrer, N.

ETH Zurich, Switzerland, November 2021 (mastersthesis)

2021

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

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

Bing, S.

ETH Zurich, Switzerland, October 2021 (mastersthesis)

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

Study of the Interventional Consistency of Autoencoders

Lanzillotta, G.

ETH Zurich, Switzerland, October 2021 (mastersthesis)

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

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

Mambelli, D.

ETH Zurich, Switzerland, October 2021 (mastersthesis)

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

Reinforcement Learning Algorithms: Analysis and Applications

Belousov, B., H., A., Klink, P., Parisi, S., Peters, J.

883, Studies in Computational Intelligence, Springer International Publishing, 2021 (book)

Belousov, B., H., A., Klink, P., Parisi, S., Peters, J. Reinforcement Learning Algorithms: Analysis and Applications 883, Studies in Computational Intelligence, Springer International Publishing, 2021 (book)

Scientific Report 2016 - 2021 [BibTex]

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.

Scientific Report 2016 - 2021 2021 (mpi_year_book)

Scientific Report 2016 - 2021 [BibTex]

2020

A Robotic Manipulation Benchmark for Causal Structure and Transfer Learning

Ahmed, O.

ETH Zurich, Switzerland, October 2020 (mastersthesis)

2020

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

A Comprehensive Benchmark Evaluation of Synthetic Data Generation for Biomedical Imaging

DuMont Schütte, A.

ETH Zurich, Switzerland, October 2020 (mastersthesis)

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

Deep learning for the parameter estimation of tight-binding Hamiltonians

Cacioppo, A.

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

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

Learning Algorithms, Invariances, and the Real World

Zecevic, M.

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

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

2019

Inferring the Band Structure from Band Mapping Data through Machine Learning

Stimper, V.

Technical University of Munich, September 2019 (mastersthesis)

2019

Stimper, V. Inferring the Band Structure from Band Mapping Data through Machine Learning Technical University of Munich, September 2019 (mastersthesis)

Learning to Diagnose Diabetes from Magnetic Resonance Tomography

Dietz, B.

ETH Zurich, Switzerland, August 2019 (mastersthesis)

Dietz, B. Learning to Diagnose Diabetes from Magnetic Resonance Tomography ETH Zurich, Switzerland, August 2019 (mastersthesis)

Automatic Segmentation and Labelling for Robot Table Tennis Time Series

Lutz, P.

Technical University Darmstadt, Germany, August 2019 (thesis)

Lutz, P. Automatic Segmentation and Labelling for Robot Table Tennis Time Series Technical University Darmstadt, Germany, August 2019 (thesis)

Reinforcement Learning for a Two-Robot Table Tennis Simulation

Li, G.

RWTH Aachen University, Germany, July 2019 (mastersthesis)

Li, G. Reinforcement Learning for a Two-Robot Table Tennis Simulation RWTH Aachen University, Germany, July 2019 (mastersthesis)

Characteristics of longitudinal physiological measurements of late-stage ALS patients

Konieczny, L.

Ludwig-Maximilians-Universität München, Germany, May 2019 (mastersthesis)

Konieczny, L. Characteristics of longitudinal physiological measurements of late-stage ALS patients Ludwig-Maximilians-Universität München, Germany, May 2019 (mastersthesis)

Scientific Report 2016 - 2018 [BibTex]

Scientific Report 2016 - 2018

2019 (mpi_year_book)

Abstract

This report presents research done at the Max Planck Institute for Intelligent Systems from January 2016 to December 2018. It is our third report since the founding of the institute in 2011. This status report is organized as follows: we begin with an overview of the institute, including its organizational structure (Chapter 1). The central part of the scientific report consists of chapters on the research conducted by the institute’s departments (Chapters 2 to 5) and its independent research groups (Chapters 6 to 18), as well as the work of the institute’s central scientific facilities (Chapter 19). For entities founded after January 2016, the respective report sections cover work done from the date of the establishment of the department, group, or facility.

Scientific Report 2016 - 2018 2019 (mpi_year_book)

Scientific Report 2016 - 2018 [BibTex]

Spatial Filtering based on Riemannian Manifold for Brain-Computer Interfacing

Xu, J.

Technical University of Munich, Germany, 2019 (mastersthesis)

Xu, J. Spatial Filtering based on Riemannian Manifold for Brain-Computer Interfacing Technical University of Munich, Germany, 2019 (mastersthesis)

2018

A virtual reality environment for experiments in assistive robotics and neural interfaces

Bustamante, S.

Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2018 (mastersthesis)

2018

Bustamante, S. A virtual reality environment for experiments in assistive robotics and neural interfaces Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2018 (mastersthesis)

On the Applicability of Machine Learning to Aid the Search for Gravitational Waves at the LIGO Experiment

Gebhard, T.

Karlsruhe Institute of Technology, Germany, 2018 (mastersthesis)

Gebhard, T. On the Applicability of Machine Learning to Aid the Search for Gravitational Waves at the LIGO Experiment Karlsruhe Institute of Technology, Germany, 2018 (mastersthesis)

A Causal Perspective on Deep Representation Learning

Suter, R.

ETH Zurich, 2018 (mastersthesis)

Suter, R. A Causal Perspective on Deep Representation Learning ETH Zurich, 2018 (mastersthesis)

Domain Adaptation Under Causal Assumptions

Lechner, T.

Eberhard Karls Universität Tübingen, Germany, 2018 (mastersthesis)

Lechner, T. Domain Adaptation Under Causal Assumptions Eberhard Karls Universität Tübingen, Germany, 2018 (mastersthesis)

Improving Tissue Differentiation based on Optical Emission Spectroscopy for Guided Electrosurgical Tumor Resection with Machine Learning

Zabel, S.

Eberhard Karls Universität Tübingen, Germany, 2018 (mastersthesis)

Zabel, S. Improving Tissue Differentiation based on Optical Emission Spectroscopy for Guided Electrosurgical Tumor Resection with Machine Learning Eberhard Karls Universität Tübingen, Germany, 2018 (mastersthesis)

Reinforcement Learning for High-Speed Robotics with Muscular Actuation

Guist, S.

Ruprecht-Karls-Universität Heidelberg , 2018 (mastersthesis)

Guist, S. Reinforcement Learning for High-Speed Robotics with Muscular Actuation Ruprecht-Karls-Universität Heidelberg , 2018 (mastersthesis)

2017

Elements of Causal Inference - Foundations and Learning Algorithms

Peters, J., Janzing, D., Schölkopf, B.

Adaptive Computation and Machine Learning Series, The MIT Press, Cambridge, MA, USA, 2017 (book)

PDF link (url) [BibTex]

2017

Peters, J., Janzing, D., Schölkopf, B. Elements of Causal Inference - Foundations and Learning Algorithms Adaptive Computation and Machine Learning Series, The MIT Press, Cambridge, MA, USA, 2017 (book)

PDF link (url) [BibTex]

Development and Evaluation of a Portable BCI System for Remote Data Acquisition

Emde, T.

Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2017 (mastersthesis)

Emde, T. Development and Evaluation of a Portable BCI System for Remote Data Acquisition Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2017 (mastersthesis)

Learning Optimal Configurations for Modeling Frowning by Transcranial Electrical Stimulation

Sücker, K.

Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2017 (mastersthesis)

Sücker, K. Learning Optimal Configurations for Modeling Frowning by Transcranial Electrical Stimulation Graduate School of Neural Information Processing, Eberhard Karls Universität Tübingen, Germany, 2017 (mastersthesis)

2015

A Cognitive Brain-Computer Interface for Patients with Amyotrophic Lateral Sclerosis

Hohmann, M.

Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

2015

Hohmann, M. A Cognitive Brain-Computer Interface for Patients with Amyotrophic Lateral Sclerosis Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

Sequential Image Deconvolution Using Probabilistic Linear Algebra

Gao, M.

Technical University of Munich, Germany, 2015 (mastersthesis)

Gao, M. Sequential Image Deconvolution Using Probabilistic Linear Algebra Technical University of Munich, Germany, 2015 (mastersthesis)

Causal Inference in Neuroimaging

Casarsa de Azevedo, L.

Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

Casarsa de Azevedo, L. Causal Inference in Neuroimaging Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

The effect of frowning on attention

Ibarra Chaoul, A.

Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

Ibarra Chaoul, A. The effect of frowning on attention Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2015 (mastersthesis)

2014

Learning Motor Skills: From Algorithms to Robot Experiments

Kober, J., Peters, J.

97, pages: 191, Springer Tracts in Advanced Robotics, Springer, 2014 (book)

2014

Kober, J., Peters, J. Learning Motor Skills: From Algorithms to Robot Experiments 97, pages: 191, Springer Tracts in Advanced Robotics, Springer, 2014 (book)

Computational Diffusion MRI and Brain Connectivity

Schultz, T., Nedjati-Gilani, G., Venkataraman, A., O’Donnell, L., Panagiotaki, E.

pages: 255, Mathematics and Visualization, Springer, 2014 (book)

Web [BibTex]

Schultz, T., Nedjati-Gilani, G., Venkataraman, A., O’Donnell, L., Panagiotaki, E. Computational Diffusion MRI and Brain Connectivity pages: 255, Mathematics and Visualization, Springer, 2014 (book)

Web [BibTex]

A Novel Causal Inference Method for Time Series

Shajarisales, N.

Eberhard Karls Universität Tübingen, Germany, Eberhard Karls Universität Tübingen, Germany, 2014 (mastersthesis)

Shajarisales, N. A Novel Causal Inference Method for Time Series Eberhard Karls Universität Tübingen, Germany, Eberhard Karls Universität Tübingen, Germany, 2014 (mastersthesis)

The Feasibility of Causal Discovery in Complex Systems: An Examination of Climate Change Attribution and Detection

Lacosse, E.

Graduate Training Centre of Neuroscience, University of Tübingen, Germany, Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2014 (mastersthesis)

Lacosse, E. The Feasibility of Causal Discovery in Complex Systems: An Examination of Climate Change Attribution and Detection Graduate Training Centre of Neuroscience, University of Tübingen, Germany, Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2014 (mastersthesis)

Causal Discovery in the Presence of Time-Dependent Relations or Small Sample Size

Huang, B.

Graduate Training Centre of Neuroscience, University of Tübingen, Germany, Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2014 (mastersthesis)

Huang, B. Causal Discovery in the Presence of Time-Dependent Relations or Small Sample Size Graduate Training Centre of Neuroscience, University of Tübingen, Germany, Graduate Training Centre of Neuroscience, University of Tübingen, Germany, 2014 (mastersthesis)