2024
ei
Park, J.
A Measure-Theoretic Axiomatisation of Causality and Kernel Regression
University of Tübingen, Germany, July 2024 (phdthesis)
ei
Sajjadi, S. M. M.
Enhancement and Evaluation of Deep Generative Networks with Applications in Super-Resolution and Image Generation
University of Tübingen, Germany, July 2024 (phdthesis)
hi
Matthew, V., Simancek, R. E., Telepo, E., Machesky, J., Willman, H., Ismail, A. B., Schulz, A. K.
Empowering Change: The Role of Student Changemakers in Advancing Sustainability within Engineering Education
Proceedings of the American Society of Engineering Education (ASEE), June 2024, Victoria Matthew and Andrew K. Schulz contributed equally to this publication. (issue) In press
ei
Stimper, V.
Advancing Normalising Flows to Model Boltzmann Distributions
University of Cambridge, UK, Cambridge, June 2024, (Cambridge-Tübingen-Fellowship-Program) (phdthesis)
ei
von Kügelgen, J.
Identifiable Causal Representation Learning
University of Cambridge, UK, Cambridge, February 2024, (Cambridge-Tübingen-Fellowship) (phdthesis)
hi
Burns, R.
Creating a Haptic Empathetic Robot Animal That Feels Touch and Emotion
University of Tübingen, Tübingen, Germany, February 2024, Department of Computer Science (phdthesis)
lds
Eberhard, O., Vernade, C., Muehlebach, M.
A Pontryagin Perspective on Reinforcement Learning
Max Planck Institute for Intelligent Systems, 2024 (techreport)
ps
Müller, L.
Self- and Interpersonal Contact in 3D Human Mesh Reconstruction
University of Tübingen, Tübingen, 2024 (phdthesis)
lds
Er, D., Trimpe, S., Muehlebach, M.
Distributed Event-Based Learning via ADMM
Max Planck Institute for Intelligent Systems, 2024 (techreport)
ps
Petrovich, M.
Natural Language Control for 3D Human Motion Synthesis
LIGM, Ecole des Ponts, Univ Gustave Eiffel, CNRS, 2024 (phdthesis)
2023
sf
Barocas, S., Hardt, M., Narayanan, A.
Fairness in Machine Learning: Limitations and Opportunities
MIT Press, December 2023 (book)
hi
Mohan, M.
Gesture-Based Nonverbal Interaction for Exercise Robots
University of Tübingen, Tübingen, Germany, October 2023, Department of Computer Science (phdthesis)
ei
Karimi, A.
Advances in Algorithmic Recourse: Ensuring Causal Consistency, Fairness, & Robustness
ETH Zurich, Switzerland, July 2023 (phdthesis)
ei
Kübler, J. M.
Learning and Testing Powerful Hypotheses
University of Tübingen, Germany, July 2023 (phdthesis)
ei
Gresele, L.
Learning Identifiable Representations: Independent Influences and Multiple Views
University of Tübingen, Germany, June 2023 (phdthesis)
ei
Paulus, M.
Learning with and for discrete optimization
ETH Zurich, Switzerland, May 2023, CLS PhD Program (phdthesis)
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
ei
Jin, Z., Mihalcea, R.
Natural Language Processing for Policymaking
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)
ev
Strecke, M. F.
Object-Level Dynamic Scene Reconstruction With Physical Plausibility From RGB-D Images
Eberhard Karls Universität Tübingen, Tübingen, 2023 (phdthesis)
ei
Berenz, V., Widmaier, F., Guist, S., Schölkopf, B., Büchler, D.
Synchronizing Machine Learning Algorithms, Realtime Robotic Control and Simulated Environment with o80
Robot Software Architectures Workshop (RSA) 2023, ICRA, 2023 (techreport)
ev
Elich, C., Kirchdorfer, L., Köhler, J. M., Schott, L.
Challenging Common Assumptions in Multi-task Learning
abs/2311.04698, CoRR/arxiv, 2023 (techreport)
mms
Schulz, Frank Martin Ernst
Static and dynamic investigation of magnonic systems: materials, applications and modeling
Universität Stuttgart, Stuttgart, 2023 (phdthesis)
2022
hi
Richardson, B.
Multi-Timescale Representation Learning of Human and Robot Haptic Interactions
University of Stuttgart, Stuttgart, Germany, December 2022, Faculty of Computer Science, Electrical Engineering and Information Technology (phdthesis)
ei
Neitz, A.
Towards learning mechanistic models at the right level of abstraction
University of Tübingen, Germany, November 2022 (phdthesis)
re
Lieder, F., Prentice, M.
Life Improvement Science
In Encyclopedia of Quality of Life and Well-Being Research, Springer, November 2022 (inbook)
ei
Lu, C.
Learning Causal Representations for Generalization and Adaptation in Supervised, Imitation, and Reinforcement Learning
University of Cambridge, UK, Cambridge, October 2022, (Cambridge-Tübingen-Fellowship) (phdthesis)
hi
Nam, S.
Understanding the Influence of Moisture on Fingerpad-Surface Interactions
University of Tübingen, Tübingen, Germany, October 2022, Department of Computer Science (phdthesis)
ei
Wenk, P.
Learning Time-Continuous Dynamics Models with Gaussian-Process-Based Gradient Matching
ETH Zurich, Switzerland, October 2022, CLS PhD Program (phdthesis)
re
Jähnichen, S., Weber, F., Prentice, M., Lieder, F.
Does deliberate prospection help students set better goals?
KogWis 2022 "Understanding Minds", September 2022 (poster) Accepted
ei
Tabibian, B.
Methods for Minimizing the Spread of Misinformation on the Web
University of Tübingen, Germany, September 2022 (phdthesis)
sf
Hardt, M., Recht, B.
Patterns, Predictions, and Actions: Foundations of Machine Learning
Princeton University Press, August 2022 (book)
ei
Huang, B.
Learning and Using Causal Knowledge: A Further Step Towards a Higher-Level Intelligence
Carnegie Mellon University, Pittsburgh, USA, July 2022 (phdthesis)
ei
Huang, B.
Learning and Using Causal Knowledge: A Further Step Towards a Higher-Level Intelligence
Carnegie Mellon University, July 2022, external supervision (phdthesis)
dlg
Ruppert, F., Badri-Spröwitz, A.
Learning Plastic Matching of Robot Dynamics in Closed-Loop Central Pattern Generators: Data
Edmond, May 2022 (techreport)
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)
dlg
pi
Badri-Spröwitz, A., Sarvestani, A. A., Sitti, M., Daley, M. A.
Data for BirdBot Achieves Energy-Efficient Gait with Minimal Control Using Avian-Inspired Leg Clutching
Edmond, March 2022 (techreport)
ei
Ialongo, A.
Variational Inference in Dynamical Systems
University of Cambridge, UK, Cambridge, February 2022, (Cambridge-Tübingen-Fellowship) (phdthesis)
ev
Li, H., Stueckler, J.
Observability Analysis of Visual-Inertial Odometry with Online Calibration of Velocity-Control Based Kinematic Motion Models
abs/2204.06651, CoRR/arxiv, 2022 (techreport)
mms
Groß, F.
Entwicklung von Methoden und Bausteinen zur Realisierung Komplexer Magnonischer Systeme
Universität Stuttgart, Stuttgart (und Cuvillier Verlag, Göttingen), 2022 (phdthesis)
al
Sun, H.
Machine-Learning-Driven Haptic Sensor Design
University of Tuebingen, Library, 2022 (phdthesis)
ei
Peters, J., Bauer, S., Pfister, N.
Causal Models for Dynamical Systems
In Probabilistic and Causal Inference: The Works of Judea Pearl, pages: 671-690, 1, Association for Computing Machinery, 2022 (inbook)
mms
Dogan, G.
Deposition and characterization of multi-functional, complex thin films using atomic layer deposition for copper corrosion protection
Universität Stuttgart, Stuttgart, 2022 (phdthesis)
ei
plg
Karimi, A. H., von Kügelgen, J., Schölkopf, B., Valera, I.
Towards Causal Algorithmic Recourse
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)
ei
Schölkopf, B.
Causality for Machine Learning
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
Salewski, L., Koepke, A. S., Lensch, H. P. A., Akata, Z.
CLEVR-X: A Visual Reasoning Dataset for Natural Language Explanations
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)
2021
pf
Qiu, T., Jeong, M., Goyal, R., Kadiri, V., Sachs, J., Fischer, P.
Magnetic Micro-/Nanopropellers for Biomedicine
In Field-Driven Micro and Nanorobots for Biology and Medicine, pages: 389-410, 16, (Editors: Sun, Y. and Wang, X. and Yu, J.), Springer Nature, November 2021 (inbook)
ics
Doerr, A.
Models for Data-Efficient Reinforcement Learning on Real-World Applications
University of Stuttgart, Stuttgart, October 2021 (phdthesis)
ei
Mehrjou, A.
Dynamics of Learning and Learning of Dynamics
ETH Zürich, Zürich, October 2021 (phdthesis)
ei
Hohmann, M.
A Large Scale Brain-Computer Interface for Patients with Neurological Diseases
University of Tübingen, Germany, September 2021 (phdthesis)
ei
Parascandolo, G.
Deep Learning Beyond The Training Distribution
ETH Zürich, Switzerland, Zürich, September 2021, (CLS Fellowship Program) (phdthesis)