Publikationen

Hier finden Sie eine umfassende Auflistung der WhiteBox-Publikationen

  • Alokla, E., Stasica, M., Puttke, M., Firouzi, V., Ahmad Sharbafi, M., & Seyfarth, A. (2025). The Effects of Imagination on Performance in Ballet: A Case Study. Sports, 13(5), Article 5. https://doi.org/10.3390/sports13050132
  • Brack, M., Katakol, S., Friedrich, F., Schramowski, P., Ravi, H., Kersting, K., & Kale, A. (2025). How to Train your Text-to-Image Model: Evaluating Design Choices for Synthetic Training Captions (No. arXiv:2506.16679). arXiv. https://doi.org/10.48550/arXiv.2506.16679
  • Busch, F. P., Zečević, M., Kersting, K., & Dhami, D. S. (2025). Elucidating linear programs by neural encodings. Frontiers in Artificial Intelligence, 8. https://doi.org/10.3389/frai.2025.1549085
  • Friedrich, F., Welsch, T. G., Brack, M., Schramowski, P., & Kersting, K. (2025). Beyond Overcorrection: Evaluating Diversity in T2I Models with DivBench (No. arXiv:2507.03015). arXiv. https://doi.org/10.48550/arXiv.2507.03015
  • Hesse, R., Fischer, J., Schaub-Meyer, S., & Roth, S. (2025). Disentangling Polysemantic Channels in Convolutional Neural Networks. Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2025, pp. 4808-4812. pdf
  • Mahmoudi, A., Khosrotabar, M., Gramann, K., Rinderknecht, S., & Sharbafi, M. A. (2025). Using Passive BCI for Personalization of Assistive Wearable Devices: A Proof-of-Concept Study. In: IEEE Transactions on Neural Systems and Rehabilitation Engineering, vol. 33, pp. 476-487, 2025, doi: 10.1109/TNSRE.2025.3530154. pdf (external)
  • Mitchell, R., Alliegro, A., Camoriano, R., Carrión-Ojeda, D., Carta, A., Chalvatzaki, G., Churamani, N., D’Eramo, C., Hamidi, S., Hesse, R., Hinder, F., Kamath, R. R., Lomonaco, V., Paul, S., Pistilli, F., Tuytelaars, T., Ven, G. M. van de, Kersting, K., Schaub-Meyer, S., & Mundt, M. (2025). Continual Learning Should Move Beyond Incremental Classification (No. arXiv:2502.11927). arXiv. https://doi.org/10.48550/arXiv.2502.11927
  • Mohseni, O., Berry, A., Schumacher, C., Seyfarth, A., Vallery, H., & Sharbafi, M. A. (2025). Muscular responses to upper body mediolateral angular momentum perturbations during overground walking. Frontiers in Bioengineering and Biotechnology, 13. https://doi.org/10.3389/fbioe.2025.1509090
  • Ott, C., Ibs, I., Rothkopf, C. A., & Jäkel, F. (2025). Towards a taxonomy of tasks for human sequential decision-making. Thinking & Reasoning, 1–35. https://doi.org/10.1080/13546783.2025.2453151 pdf (external)
  • Ott, C., & Jäkel, F. (2025). Types of Relations: Defining Analogies with Category Theory (No. arXiv:2505.19792). arXiv. https://doi.org/10.48550/arXiv.2505.19792
  • Schuhmann, C., Kaczmarczyk, R., Rabby, G., Friedrich, F., Kraus, M., Kalyan, K., Nadi, K., Nguyen, H., Kersting, K., & Auer, S. (2025). EmoNet-Face: An Expert-Annotated Benchmark for Synthetic Emotion Recognition (No. arXiv:2505.20033). arXiv. https://doi.org/10.48550/arXiv.2505.20033
  • Schuhmann, C., Kaczmarczyk, R., Rabby, G., Friedrich, F., Kraus, M., Nadi, K., Nguyen, H., Kersting, K., & Auer, S. (2025). EmoNet-Voice: A Fine-Grained, Expert-Verified Benchmark for Speech Emotion Detection (No. arXiv:2506.09827). arXiv. https://doi.org/10.48550/arXiv.2506.09827
  • Schultheis, M. (2025). Inverse Reinforcement Learning for Human Decision-Making Under Uncertainty. [Doctoral dissertation, Technical University Darmstadt]. https://tuprints.ulb.tu-darmstadt.de/29974/
  • Steinmann, D., Stammer, W., Wüst, A., & Kersting, K. (2025). Object Centric Concept Bottlenecks (No. arXiv:2505.24492). arXiv. https://doi.org/10.48550/arXiv.2505.24492
  • Ye, Z., Arenz, O., & Kersting, K. (2025). Learning from Less: Guiding Deep Reinforcement Learning with Differentiable Symbolic Planning (No. arXiv:2505.11661). arXiv. https://doi.org/10.48550/arXiv.2505.11661
  • Yu, Z. (2025). Probabilistic Circuits: Going Bayesian and Spectral with Densities and Time Series [Dissertation, Technical University Darmstadt]. https://doi.org/10.26083/tuprints-00029890
  • Andreu, M. G., Ploeger, K., & Peters, J. (2024). Beyond the Cascade: Juggling Vanilla Siteswap Patterns. Proceedings of 2024 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) October 14-18, 2024, Abu Dhabi, UAE pdf (external)
  • Behrens, T., Kühn, A. & Jäkel, F. (2024). Connecting process models to response times through Bayesian hierarchical regression analysis. Behavior Research Methods 56, 6951–6966 (2024). pdf (external)
  • Brack, M., Friedrich, F., Kornmeier, K., Tsaban, L., Schramowski, P., Kersting, K., & Passos, A. (2024). Ledits++: Limitless image editing using text-to-image models. In Proceedings of the IEEE/CVF conference on computer vision and pattern recognition (pp. 8861-8870). pdf (external)
  • Braun, S., Mundt, M., & Kersting, K. (2024). Deep Classifier Mimicry without Data Access. In the Proceedings of The 27th International Conference on Artificial Intelligence and Statistics, PMLR 238:4762-4770, 2024. pdf (external)
  • Busch, F. P., Kamath, R., Mitchell, R., Stammer, W., Kersting, K., & Mundt, M. (2024). Where is the Truth? The Risk of Getting Confounded in a Continual World. https://arxiv.org/abs/2402.06434
  • Delfosse, Q., Sztwiertnia, S., Rothermel, M., Stammer, W., & Kersting, K. (2024). Interpretable concept bottlenecks to align reinforcement learning agents. Advances in Neural Information Processing Systems, 37, 66826-66855. pdf (external)
  • Depeweg, S., Rothkopf, C. A., & Jäkel, F. (2024). Solving bongard problems with a visual language and pragmatic constraints. Cognitive Science, 48(5), e13432. pdf (external)
  • Dotterer, S., Ibs, I., Rothkopf, C. A. (2024) Human Strategies for Optimization under Constraints, Interdisciplinary College 2024
  • Drewing, N., Ahmadi, A., Xiong, X., & Sharbafi, M. A. (2024). Comparison of Empirical and Reinforcement Learning (RL)-Based Control Based on Proximal Policy Optimization (PPO) for Walking Assistance: Does AI Always Win?. In: Biomimetics, 2024, 9 (11), p.665. doi: 10.26083/tuprints-00028848 TUprints pdf (external)
  • Firouzi, V., Mohseni, O., Seyfarth, A., von Stryk, O., & Sharbafi, M. A. (2024). Exploring the control of whole-body angular momentum in young and elderly based on the virtual pivot point concept. Royal Society of Open Science, 11:240273. https://doi.org/10.1098/rsos.240273. pdf (external)
  • Friedrich, F., Tedeschi, S., Schramowski, P., Brack, M., Navigli, R., Nguyen, H., Li, B., & Kersting, K. (2025). LLMs Lost in Translation: M-ALERT uncovers Cross-Linguistic Safety Inconsistencies. arXiv. https://doi.org/10.48550/arXiv.2412.15035
  • Härle, R., Friedrich, F., Brack, M., Deiseroth, B., Schramowski, P., & Kersting, K. (2024). SCAR: Sparse Conditioned Autoencoders for Concept Detection and Steering in LLMs. arXiv. https://doi.org/10.48550/arXiv.2411.07122
  • Helff, L., Friedrich, F., Brack, M., Schramowski, P., & Kersting, K. (2024). LLAVAGUARD: VLM-based Safeguard for Vision Dataset Curation and Safety Assessment. In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (pp. 8322-8326). pdf (external)
  • Ibs, I., Ott, C., Jäkel, F., and Rothkopf, C. A. (2024). From Human Explanations to Explainable AI: Insights from Constrained Optimization. Cognitive Systems Research, Volume 88, December 2024, 101297. pdf (external)
  • Ibs, I., Ott, C., Rothkopf, C., & Jäkel, F. (2024). Task Diversity and Human Decision-Making: A Taxonomic View. Proceedings of the Annual Meeting of the Cognitive Science Society, 46(0). https://escholarship.org/uc/item/2b3990kf
  • Ibs, I., Schäfer, J., & Rothkopf, C. A. (2024). Exploring How Information Shapes Human Inference from Demonstrations. Computational Cognitive Neuroscience (CCN 2024 Boston)
  • Kamath, R., Mitchell, R., Paul, S., Kersting, K., & Mundt, M. (2024). BOWLL: A Deceptively Simple Open World Lifelong Learner. https://arxiv.org/abs/2402.04814
  • Khosrotabar, M., Mahmoudi, A., Sharbafi, M. (2024). Passive BCI Feasibility in Evaluating Knee Exoskeleton Assistance. Mobile Brain Body Imaging Conference 2024, Piran, Slovenia.
  • Kornmann, M., He, Q., Kshirsagar, A., Ploeger, K. & Peters, J. (2024). Learning to Accurately Throw Paper Planes. In Proceedings of: 8th Annual Conference on Robot Learning (CoRL 2024) pdf (external)
  • Mahmoudi, A., Khosrotabar, A., Kuhmann, J., Grimmer, M., Rinderknecht, S., & Sharbafi, M. A. (2024). Feasibility of Utilizing Passive BCI for Assistance Evaluation: A Case Study on a Knee Exoskeleton. Proceedings of 2024 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob), pp. 235-242, doi: 10.1109/BioRob60516.2024.10719932. pdf (external)
  • Mohseni, O., Mahmoudi, A., Firouzi, V., Seyfarth, A., Vallery, H., & Sharbafi, M. A. (2024). Balance recovery schemes following mediolateral gyroscopic moment perturbations during walking. PLOS ONE 19(12): e0315414. https://doi.org/10.1371/journal.pone.0315414 pdf (external)
  • Nejad, A. M., Sharbafi, M. A., Mohseni, O., & Seyfarth, A. (2024). Role of compliant mechanics and motor control in hopping – from human to robot. Sci Rep 14, 6820 (2024). https://doi.org/10.1038/s41598-024-57149-0
  • Ott, C. (2024). Structural Similarity: Formalizing Analogies using Category Theory. In the Proceedings of 35th European Summer School in Logic, Language and Information (ESSLLI 2024) pdf (external)
  • Ott, C. and Jäkel, F. (2024). SimplifEx: Simplifying and Explaining Linear Programs. Cognitive Systems Research. Cognitive Systems Research, Volume 88, December 2024, 101298. https://doi.org/10.1016/j.cogsys.2024.101298 pdf (external)
  • Ott, C., & Jäkel, F. Parsing Predicates: Exploring Analogies through the Lens of Category Theory. Fifth International Conference on Analogy (Analogy 2024) Amsterdam, The Netherlands.
  • Poonia, H., Willig, M., Yu, Z., Zečević, M., Kersting, K., & Dhami, D. S. (2024). ΧSPN: characteristic interventional sum-product networks for causal inference in hybrid domains. In Proceedings of the 40th Conference on Uncertainty in Artificial Intelligence (UAI '24), Vol. 244. JMLR.org, Article 140, 3004–3020. pdf (external)
  • Rashty A. M. N., Sharbafi, M. A., Mohseni, O., & Seyfarth, A. (2024). Role of compliant mechanics and motor control in hopping – from human to robot. Scientific Report, Nature, vol. 14, No. 1, p. 6820, 2024 pdf (external)
  • Rashty, A. M. N., Sharbafi, M. A. , & Seyfarth, A. (2024). Variability in hopping is largely individual and reduced by a metronome. Proceedings of 2024 10th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob) pdf (external)
  • Reining​, L. C. , & Wallis​, T. S. A. (2024). A psychophysical evaluation of techniques for Mooney image generation. PeerJ 12:e18059. https://doi.org/10.7717/peerj.18059 pdf (external)
  • Reining, L., Turon, R., Hummel, P., Radatz, F. , Lind, C., Yu, A., Jäkel, F., & Wallis, T. S.A. (2024). Bayesian adaptive estimation of high-dimensional psychometric functions: A particle filtering approach. VSS '24: 24th Annual Meeting of the Vision Sciences Society, Florida. Journal of Vision 2024;24(10):878. https://doi.org/10.1167/jov.24.10.878
  • Stammer, W., Wüst, A., Steinmann, D., & Kersting, K. (2024). Neural Concept Binder. In Proceedings of 38th Conference on Neural Information Processing Systems (NeurIPS 2024). pdf (external)
  • Steinmann, D., Zečević, M., Dhami, D. S., & Kersting, K. (2024). We Should Care about Explaining Even Linear Programs. Authorea. https://doi.org/10.22541/au.172833619.95560618/v1
  • Thomas, T., Straub, D., Tatai, F., Shene, M., Tosik, T., Kersting, K., & Rothkopf C. A. (2024). Modelling dataset bias in machine-learned theories of economic decision-making. Nature Human Behavior 8, 679–691 (2024). https://doi.org/10.1038/s41562-023-01784-6 pdf (external)
  • Turon, R., Reining, L., Wallis, T. S. A., & Jäkel, F. (2024). Stimulus distributions affect uncertainty sampling approaches to adaptive estimation of classification images. VSS '24: 24th Annual Meeting of the Vision Sciences Society, Florida. Journal of Vision 2024, 24(10):869. https://doi.org/10.1167/jov.24.10.869
  • Zečević, M., Dhami, D. S., & Kersting, K. (2024). Structural causal models reveal confounder bias in linear program modelling. Machine Learning, 113(3), 1329-1349. https://doi.org/10.1007/s10994-023-06431-9. pdf (external)
  • Brack, M., Schramowski, P., Deiseroth, B., & Kersting, K. (2023). ILLUME: Rationalizing Vision-Language Models through Human Interactions. pdf (wird in neuem Tab geöffnet) (external)
    In Proceedings of the 40th International Conference on Machine Learning (ICML).
  • Dill, S., Li, S.Z., Rohr, M., Sharbafi, M., & Antink, C.H. (2023). Automatic Generation of Labeled Data for Video-Based Human Pose Analysis via NLP applied to YouTube Subtitles. pdf (external)
    45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC), doi: 10.1109/EMBC40787.2023.10340044.
  • Friedrich, F., Stammer, W., Schramowski, P., Kersting, K. (2023). A typology for exploring the mitigation of shortcut behaviour. pdf (external)
    Nature Machine Intelligence 5:319-330.
  • Hesse, R., Schaub-Meyer, S., & Roth, S (2023). Content-Adaptive Downsampling in Convolutional Neural Networks. pdf (wird in neuem Tab geöffnet) (external)
    Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, 2023, pp. 4544-4553
  • Kadner, F., Thomas, T., Hoppe, D., Rothkopf, C. A. (2023). Improving saliency models’ predictions of the next fixation with humans’ intrinsic cost of gaze shifts. pdf (wird in neuem Tab geöffnet) (external)
    Proceedings of 2023 IEEE/CVF Winter Conference on Applications of Computer Vision (WACV)
  • Scholl, P., Firouzi, V., Karimi, M.T., Seyfarth, A., Sharbafi, M.A.(2023). Virtual Pivot Point Model Predicts Instability in Parkinsonian Gaits. pdf (external)
    2023 IEEE International Conference on Systems, Man, and Cybernetics (SMC), pp. 5261-5266, doi: 10.1109/SMC53992.2023.10394155.
  • Schramowski, P., Brack, M., Deiseroth, B., & Kersting, K. (2023). Safe Latent Diffusion: Mitigating Inappropriate Degeneration in Diffusion Models. pdf (wird in neuem Tab geöffnet) (external)
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
  • Schultze, S., Withöft, A., Abdenebaoui, L., & Boll, S. (2023). Explaining Image Aesthetics Assessment: An Interactive Approach. pdf (external)
    In Proceedings of the 2023 ACM International Conference on Multimedia Retrieval (ICMR '23).
  • Sidheekh, S., Kersting, K., & Natarajan, S. (2023). Probabilistic Flow Circuits: Towards Unified Deep Models for Tractable Probabilistic Inference. pdf (wird in neuem Tab geöffnet) (external)
    In Proceedings of the 39th Conference on Uncertainty in Artificial Intelligence (UAI).
  • Skryagin, A., Ochs, D., Dhami, D.S., & Kersting, K. (2023). Scalable Neural-Probabilistic Answer Set Programming. pdf (external)
    Journal of Artificial Intelligence Research (JAIR) 78:579–617.
  • Straub, D., Schultheis, M., Koeppl, H., & Rothkopf, C. A. (2023). Probabilistic inverse optimal control for non-linear partially observable systems disentangles perceptual uncertainty and behavioral costs. pdf (wird in neuem Tab geöffnet) (external)
    In Advances in Neural Information Processing Systems (NeurIPS 2023), 36.
  • Ventola, F., Braun, S., Yu, Z., Mundt, M., & Kersting, K. (2023). Probabilistic Circuits That Know What They Don't Know. pdf (wird in neuem Tab geöffnet) (external)
    In Proceedings of the 39th Conference on Uncertainty in Artificial Intelligence (UAI).
  • Willig, M., Zečević, M., Dhami, D.S., & Kersting, K. (2023). Do Not Marginalize Mechanisms, Rather Consolidate!. pdf (external)
    In Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS).
  • Yu, Z., Trapp, M., & Kersting, K. (2023). Characteristic Circuits. pdf (external)
    In Proceedings of the 37th Conference on Neural Information Processing Systems (NeurIPS).
  • Zečević, M., Dhami, D.S., Kersting, K. (2023). Not All Causal Inference is the Same. pdf (external)
    Transactions on Machine Learning Research (TMLR).
  • Zečević, M., Willig, M., Dhami, D.S., & Kersting, K. (2023). Causal Parrots. Large Language Models May Talk Causality But Are Not Causal. pdf (external)
    Transactions on Machine Learning Research (TMLR).
  • Firouzi, V., Mohseni, O., Sharbafi, MA. (2022). Model-based Control for Gait Assistance in the Frontal Plane.
    2022 9th IEEE RAS/EMBS International Conference for Biomedical Robotics and Biomechatronics (BioRob)
  • Mohseni, O., Schmidt, P., Seyfarth, A., Sharbafi, MA. (2022). Unified GRF-based control for adjusting hopping frequency with various robot configurations.
    In: Journal of Advanced Robotics, Volume 36, 2022 – Issue 13, Special Issue on Adaptive Motion of Animals and Machines.
  • Ploeger, K., Peters, J. (2022). Controlling the cascade: Kinematic planning for n-ball toss juggling. pdf (wird in neuem Tab geöffnet) (external)
    IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS))
  • Schramowski, P., Turan, C., Andersen, N., Rothkopf, C. A., & Kersting, K. (2022). Large pre-trained language models contain human-like biases of what is right and wrong to do. pdf (wird in neuem Tab geöffnet) (external)
    Nature Machine Intelligence, 4(3), 258-268
  • Schultheis, M., Rothkopf, C. A., & Koeppl, H. (2022). Reinforcement Learning with Non-Exponential Discounting. pdf (wird in neuem Tab geöffnet) (external)
    Advances in Neural Information Processing Systems, 35, 3649-3662.
  • Skryagin, A., Stammer, W., Ochs, D., Singh Dhami, D., Kersting, K. (2022). Neural-Probabilistic Answer Set Programming. pdf (wird in neuem Tab geöffnet) (external)
    In Proceedings of the 19th International Conference on Principles of Knowledge Representation and Reasoning (KR).
  • Stammer, W., Memmel, M., Schramowski, P., Kersting, K. (2022). Interactive Disentanglement: Learning Concepts by Interacting with their Prototype Representations. pdf (wird in neuem Tab geöffnet) (external)
    In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)
  • Straub, D., Schultheis, M., & Rothkopf, C. A. (2022). Inferring implicit sensorimotor costs by inverse optimal control with signal dependent noise. pdf (wird in neuem Tab geöffnet) (external)
    Computational and Systems Neuroscience (COSYNE)
  • Thomas, T., Hoppe, D., & Rothkopf, C. A. (2022). The neuroeconomics of individual differences in saccadic decisions. bioRxiv. https://doi.org/10.1101/2022.06.03.494508
  • Trick, S., Rothkopf, S.A. (2022). Bayesian classifier fusion with an explicit model of correlation. pdf (wird in neuem Tab geöffnet) (external)
    International Conference on Artificial Intelligence and Statistics (AISTATS), PMLR 151:2282-2310, 2022
  • Yu, Z., Ventola, F., Thoma, N., Singh Dhami, D., Mundt, M., Kersting, K. (2022): Predictive Whittle Networks for Time Series. pdf (external)
    In Proceedings of the 38th Conference on Uncertainty in Artificial Intelligence (UAI), PMLR 180:2320-2330.
  • Zečević, M., Busch, F. P., Dhami, D. S., & Kersting, K. (2022, March 25). Finding Structure and Causality in Linear Programs. ICLR2022 Workshop on the Elements of Reasoning: Objects, Structure and Causality. https://openreview.net/forum?id=rc8l8SOU9ec
  • Schultheis, M., Straub, D., Rothkopf, C.A. (2021).
    Inverse Optimal Control Adapted to the Noise Characteristics of the Human Sensorimotor System. pdf (wird in neuem Tab geöffnet) (external)
    Pre-proceedings of Advances in Neural Information Processing Systems 34 (NeurIPS 2021)
  • Stammer, W., Schramowski, P., & Kristian Kersting. (2021).
    Right for the Right Concept: Revising Neuro-Symbolic Concepts by Interacting with their Explanations. pdf (wird in neuem Tab geöffnet) (external)
    Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).
  • Ventola, F., Dhami, D. S., & Kristian Kersting. (2021).
    Generative Clausal Networks: Relational Decision Trees as Probabilistic Circuits. pdf (wird in neuem Tab geöffnet) (external)
    Proceedings of the 30th International Conference on Inductive Logic Programming (ILP).
  • Yu, Z., Ventola, F., & Kristian Kersting. (2021).
    Whittle Networks: A Deep Likelihood Model for Time Series. pdf (wird in neuem Tab geöffnet) (external)
    Proceedings of the 38th International Conference on Machine Learning (ICML) , 12177–12186.
  • Yu, Z., Zhu, M., Trapp, M., Skryagin, A., & Kristian Kersting. (2021).
    Leveraging Probabilistic Circuits for Nonparametric Multi-Output Regression. pdf (wird in neuem Tab geöffnet) (external)
    Proceedings of the 37th Conference on Uncertainty in Artificial Intelligence (UAI).
  • Zečević, M., Dhami, D. S., Karanam, A., Natarajan, S., & Kristian Kersting. (2021).
    Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models. pdf (wird in neuem Tab geöffnet) (external)
    Proceedings of the 34th Conference on Neural Information Processing Systems (NeurIPS 2021).