Efficient and Sustainable AI

📝 Publications and preprints

Preprints

1. Fayad, I., Zimmer, M., Schwartz, M., Ciais, P., Gieseke, F., Belouze, G., Brood, S., De Truchis, A., and d’Aspremont, A. (2025). DUNIA: Pixel-Sized Embeddings Via Cross-Modal Alignment for Earth Observation Applications. [arXiv]
   [BibTeX]

   @misc{2025_IbrahimEtAl_DuniaCrossmodalalignment,
     archiveprefix = {arXiv},
     eprint = {2502.17066},
     primaryclass = {cs.CV},
     year = {2025},
     author = {Fayad, Ibrahim and Zimmer, Max and Schwartz, Martin and Ciais, Philippe and Gieseke, Fabian and Belouze, Gabriel and Brood, Sarah and De Truchis, Aurelien and d'Aspremont, Alexandre},
     title = {DUNIA: Pixel-Sized Embeddings Via Cross-Modal Alignment for Earth Observation Applications},
     date = {2025-02-24}
   }

2. Pauls, J., Zimmer, M., Turan, B., Saatchi, S., Ciais, P., Pokutta, S., and Gieseke, F. (2025). Capturing Temporal Dynamics in Large-Scale Canopy Tree Height Estimation. [arXiv]
   [BibTeX]

   @misc{2025_JanEtAl_Temporalcanopyheight,
     archiveprefix = {arXiv},
     eprint = {2501.19328},
     primaryclass = {cs.LG},
     year = {2025},
     author = {Pauls, Jan and Zimmer, Max and Turan, Berkant and Saatchi, Sassan and Ciais, Philippe and Pokutta, Sebastian and Gieseke, Fabian},
     title = {Capturing Temporal Dynamics in Large-Scale Canopy Tree Height Estimation},
     date = {2025-01-31}
   }

3. Mundinger, K., Zimmer, M., Kiem, A., Spiegel, C., and Pokutta, S. (2025). Neural Discovery in Mathematics: Do Machines Dream of Colored Planes? [arXiv]
   [BibTeX]

   @misc{2025_MundingerZimmerKiemSpiegelPokutta_NeuralDiscovery,
     archiveprefix = {arXiv},
     eprint = {2501.18527},
     primaryclass = {cs.LG},
     year = {2025},
     author = {Mundinger, Konrad and Zimmer, Max and Kiem, Aldo and Spiegel, Christoph and Pokutta, Sebastian},
     title = {Neural Discovery in Mathematics: Do Machines Dream of Colored Planes?},
     date = {2025-01-30}
   }

4. Pelleriti, N., Zimmer, M., Wirth, E., and Pokutta, S. (2025). Approximating Latent Manifolds in Neural Networks Via Vanishing Ideals. [arXiv]
   [BibTeX]

   @misc{2025_PelleritiZimmerWirthPokutta_Latentmanifolds,
     archiveprefix = {arXiv},
     eprint = {2502.15051},
     primaryclass = {cs.LG},
     year = {2025},
     author = {Pelleriti, Nico and Zimmer, Max and Wirth, Elias and Pokutta, Sebastian},
     title = {Approximating Latent Manifolds in Neural Networks Via Vanishing Ideals},
     date = {2025-02-20}
   }

5. Göß, A., Martin, A., Pokutta, S., and Sharma, K. (2023). Norm-induced Cuts: Optimization with Lipschitzian Black-box Functions. [URL] [arXiv]
   [BibTeX]

   @misc{2024_AdrianMartinPokuttaSharma_Norminducedcuts,
     url = {https://opus4.kobv.de/opus4-trr154/files/518/nic_preprint.pdf},
     archiveprefix = {arXiv},
     eprint = {2403.11546},
     primaryclass = {math.OC},
     year = {2024},
     author = {Göß, Adrian and Martin, Alexander and Pokutta, Sebastian and Sharma, Kartikey},
     title = {Norm-induced Cuts: Optimization with Lipschitzian Black-box Functions},
     date = {2023-05-16}
   }

6. Goerigk, M., Hartisch, M., Merten, S., and Sharma, K. (2024). Feature-Based Interpretable Optimization. [arXiv]
   [BibTeX]

   @misc{2024_GoerigkHartischMertenSharma_Featureinterpretableoptimization,
     archiveprefix = {arXiv},
     eprint = {2409.01869},
     primaryclass = {math.OC},
     year = {2024},
     author = {Goerigk, Marc and Hartisch, Michael and Merten, Sebastian and Sharma, Kartikey},
     title = {Feature-Based Interpretable Optimization},
     date = {2024-09-03}
   }

7. Mundinger, K., Zimmer, M., and Pokutta, S. (2024). Neural Parameter Regression for Explicit Representations of PDE Solution Operators. [arXiv]
   [BibTeX]

   @misc{2024_MundingerZimmerPokutta_Neuralparameterregression,
     archiveprefix = {arXiv},
     eprint = {2403.12764},
     primaryclass = {cs.LG},
     year = {2024},
     author = {Mundinger, Konrad and Zimmer, Max and Pokutta, Sebastian},
     title = {Neural Parameter Regression for Explicit Representations of PDE Solution Operators},
     date = {2024-03-19}
   }

8. Haase, J., and Pokutta, S. (2024). Human-AI Co-Creativity: Exploring Synergies Across Levels of Creative Collaboration. [arXiv]
   [BibTeX]

   @misc{2024_Pokutta_HumanAICOcreative,
     archiveprefix = {arXiv},
     eprint = {2411.12527},
     primaryclass = {cs.HC},
     year = {2024},
     author = {Haase, Jennifer and Pokutta, Sebastian},
     title = {Human-AI Co-Creativity: Exploring Synergies Across Levels of Creative Collaboration},
     date = {2024-11-19}
   }

9. Zimmer, M., Andoni, M., Spiegel, C., and Pokutta, S. (2023). PERP: Rethinking the Prune-Retrain Paradigm in the Era of LLMs. [arXiv] [code]
   [BibTeX]

   @misc{2023_ZimmerAndoniSpiegelPokutta_PerpPruneRetrain,
     archiveprefix = {arXiv},
     eprint = {2312.15230},
     primaryclass = {cs.LG},
     year = {2023},
     author = {Zimmer, Max and Andoni, Megi and Spiegel, Christoph and Pokutta, Sebastian},
     title = {PERP: Rethinking the Prune-Retrain Paradigm in the Era of LLMs},
     code = {https://github.com/ZIB-IOL/PERP},
     date = {2023-12-23}
   }

10. Zimmer, M., Spiegel, C., and Pokutta, S. (2022). Compression-aware Training of Neural Networks Using Frank-Wolfe. [arXiv]
    [BibTeX]

    @misc{2022_ZimmerSpiegelPokutta_Compressionawaretraining,
      archiveprefix = {arXiv},
      eprint = {2205.11921},
      primaryclass = {cs.LG},
      year = {2022},
      author = {Zimmer, Max and Spiegel, Christoph and Pokutta, Sebastian},
      title = {Compression-aware Training of Neural Networks Using Frank-Wolfe},
      date = {2022-05-24}
    }

11. Carderera, A., Pokutta, S., Schütte, C., and Weiser, M. (2021). CINDy: Conditional Gradient-based Identification of Non-linear Dynamics – Noise-robust Recovery. [arXiv]
    [BibTeX]

    @misc{2021_CardereraPokuttaSchutteWeiser_CINDy,
      archiveprefix = {arXiv},
      eprint = {2101.02630},
      primaryclass = {math.DS},
      year = {2021},
      author = {Carderera, Alejandro and Pokutta, Sebastian and Schütte, Christof and Weiser, Martin},
      title = {CINDy: Conditional Gradient-based Identification of Non-linear Dynamics -- Noise-robust Recovery},
      date = {2021-01-07}
    }

12. Combettes, C., Spiegel, C., and Pokutta, S. (2020). Projection-free Adaptive Gradients for Large-scale Optimization. [arXiv] [summary] [code]
    [BibTeX]

    @misc{2020_CombettesSpiegelPokutta_Projectionfreeadaptivegradients,
      archiveprefix = {arXiv},
      eprint = {2009.14114},
      primaryclass = {math.OC},
      year = {2020},
      author = {Combettes, Cyrille and Spiegel, Christoph and Pokutta, Sebastian},
      title = {Projection-free Adaptive Gradients for Large-scale Optimization},
      code = {https://github.com/ZIB-IOL/StochasticFrankWolfe},
      summary = {https://pokutta.com/blog/research/2020/10/21/adasfw.html},
      date = {2020-09-29}
    }

13. Pokutta, S., Spiegel, C., and Zimmer, M. (2020). Deep Neural Network Training with Frank-Wolfe. [arXiv] [summary] [code]
    [BibTeX]

    @misc{2020_PokuttaSpiegelZimmer_Frankwolfeneuralnetworks,
      archiveprefix = {arXiv},
      eprint = {2010.07243},
      primaryclass = {cs.LG},
      year = {2020},
      author = {Pokutta, Sebastian and Spiegel, Christoph and Zimmer, Max},
      title = {Deep Neural Network Training with Frank-Wolfe},
      code = {https://github.com/ZIB-IOL/StochasticFrankWolfe},
      summary = {https://pokutta.com/blog/research/2020/11/11/NNFW.html},
      date = {2020-10-14}
    }

Conference proceedings

1. Sadiku, S., Wagner, M., and Pokutta, S. (2023, November 29). Group-wise Sparse and Explainable Adversarial Attacks. Proceedings of the International Conference on Learning Representations. [arXiv]
   [BibTeX]

   @inproceedings{2023_SadikuWagnerPokutta_Groupwisesparseattacks,
     year = {2025},
     booktitle = {Proceedings of the International Conference on Learning Representations},
     archiveprefix = {arXiv},
     eprint = {2311.17434},
     primaryclass = {cs.CV},
     author = {Sadiku, Shpresim and Wagner, Moritz and Pokutta, Sebastian},
     title = {Group-wise Sparse and Explainable Adversarial Attacks},
     date = {2023-11-29}
   }

2. Głuch, G., Turan, B., Nagarajan, S. G., and Pokutta, S. (2024, October 11). The Good, the Bad and the Ugly: Watermarks, Transferable Attacks and Adversarial Defenses. Proceedings of the ICLR Workshop on GenAI Watermarking. [arXiv]
   [BibTeX]

   @inproceedings{2024_GrzegorzTuranNagarajanPokutta_Watermarksadversarialdefenses,
     year = {2025},
     booktitle = {Proceedings of the ICLR Workshop on GenAI Watermarking},
     archiveprefix = {arXiv},
     eprint = {2410.08864},
     primaryclass = {cs.LG},
     author = {Głuch, Grzegorz and Turan, Berkant and Nagarajan, Sai Ganesh and Pokutta, Sebastian},
     title = {The Good, the Bad and the Ugly: Watermarks, Transferable Attacks and Adversarial Defenses},
     date = {2024-10-11}
   }

3. Hollender, A., Maystre, G., and Nagarajan, S. G. (2024, September 11). The Complexity of Two-Team Polymatrix Games with Independent Adversaries. Proceedings of the International Conference on Learning Representations. [arXiv]
   [BibTeX]

   @inproceedings{2024_HollenderMaystreNagarajan_Twoteampolymatrix,
     year = {2025},
     booktitle = {Proceedings of the International Conference on Learning Representations},
     archiveprefix = {arXiv},
     eprint = {2409.07398},
     primaryclass = {cs.GT},
     author = {Hollender, Alexandros and Maystre, Gilbert and Nagarajan, Sai Ganesh},
     title = {The Complexity of Two-Team Polymatrix Games with Independent Adversaries},
     date = {2024-09-11}
   }

4. Roux, C., Zimmer, M., and Pokutta, S. (2024, February 19). On the Byzantine-resilience of Distillation-based Federated Learning. Proceedings of the International Conference on Learning Representations. [arXiv]
   [BibTeX]

   @inproceedings{2024_RouxZimmerPokutta_Byzantineresilience,
     year = {2025},
     booktitle = {Proceedings of the International Conference on Learning Representations},
     archiveprefix = {arXiv},
     eprint = {2402.12265},
     primaryclass = {cs.LG},
     author = {Roux, Christophe and Zimmer, Max and Pokutta, Sebastian},
     title = {On the Byzantine-resilience of Distillation-based Federated Learning},
     date = {2024-02-19}
   }

5. Sadiku, S., Wagner, M., Nagarajan, S. G., and Pokutta, S. (2024, October 21). S-CFE: Simple Counterfactual Explanations. Proceedings of the International Conference on Artificial Intelligence and Statistics. [arXiv]
   [BibTeX]

   @inproceedings{2024_SadikuEtAl_Counterfactualexplanations,
     year = {2025},
     booktitle = {Proceedings of the International Conference on Artificial Intelligence and Statistics},
     archiveprefix = {arXiv},
     eprint = {2410.15723},
     primaryclass = {cs.LG},
     author = {Sadiku, Shpresim and Wagner, Moritz and Nagarajan, Sai Ganesh and Pokutta, Sebastian},
     title = {S-CFE: Simple Counterfactual Explanations},
     date = {2024-10-21}
   }

6. Wäldchen, S., Sharma, K., Turan, B., Zimmer, M., and Pokutta, S. (2022, June 1). Interpretability Guarantees with Merlin-Arthur Classifiers. Proceedings of the International Conference on Artificial Intelligence and Statistics. [arXiv]
   [BibTeX]

   @inproceedings{2022_WaeldchenEtAl_Interpretabilityguarantees,
     year = {2024},
     booktitle = {Proceedings of the International Conference on Artificial Intelligence and Statistics},
     archiveprefix = {arXiv},
     eprint = {2206.00759},
     primaryclass = {cs.LG},
     author = {Wäldchen, Stephan and Sharma, Kartikey and Turan, Berkant and Zimmer, Max and Pokutta, Sebastian},
     title = {Interpretability Guarantees with Merlin-Arthur Classifiers},
     date = {2022-06-01}
   }

7. Zimmer, M., Spiegel, C., and Pokutta, S. (2023, June 29). Sparse Model Soups: A Recipe for Improved Pruning Via Model Averaging. Proceedings of the International Conference on Learning Representations. [URL] [arXiv]
   [BibTeX]

   @inproceedings{2023_ZimmerSpiegelPokutta_Sparsemodelsoups,
     year = {2024},
     booktitle = {Proceedings of the International Conference on Learning Representations},
     url = {https://iclr.cc/virtual/2024/poster/17433},
     archiveprefix = {arXiv},
     eprint = {2306.16788},
     primaryclass = {cs.LG},
     author = {Zimmer, Max and Spiegel, Christoph and Pokutta, Sebastian},
     title = {Sparse Model Soups: A Recipe for Improved Pruning Via Model Averaging},
     date = {2023-06-29}
   }

8. Mundinger, K., Pokutta, S., Spiegel, C., and Zimmer, M. (2024, April 8). Extending the Continuum of Six-Colorings. Proceedings of the Discrete Mathematics Days. [URL] [arXiv]
   [BibTeX]

   @inproceedings{2024_MundingerPokuttaSpiegelZimmer_SixcoloringsExpansion:1,
     year = {2024},
     booktitle = {Proceedings of the Discrete Mathematics Days},
     url = {https://dmd2024.web.uah.es/files/abstracts/paper_27.pdf},
     archiveprefix = {arXiv},
     eprint = {2404.05509},
     primaryclass = {math.CO},
     author = {Mundinger, Konrad and Pokutta, Sebastian and Spiegel, Christoph and Zimmer, Max},
     title = {Extending the Continuum of Six-Colorings},
     date = {2024-04-08}
   }

9. Pauls, J., Zimmer, M., Kelly, U. M., Schwartz, M., Saatchi, S., Ciais, P., Pokutta, S., Brandt, M., and Gieseke, F. (2024, June 3). Estimating Canopy Height at Scale. Proceedings of the International Conference on Machine Learning. [arXiv] [code]
   [BibTeX]

   @inproceedings{2024_PaulsEtAl_Canopyheightestimation,
     year = {2024},
     booktitle = {Proceedings of the International Conference on Machine Learning},
     archiveprefix = {arXiv},
     eprint = {2406.01076},
     primaryclass = {cs.CV},
     author = {Pauls, Jan and Zimmer, Max and Kelly, Una M and Schwartz, Martin and Saatchi, Sassan and Ciais, Philippe and Pokutta, Sebastian and Brandt, Martin and Gieseke, Fabian},
     title = {Estimating Canopy Height at Scale},
     code = {https://github.com/AI4Forest/Global-Canopy-Height-Map},
     date = {2024-06-03}
   }

10. Zimmer, M., Spiegel, C., and Pokutta, S. (2021, November 1). How I Learned to Stop Worrying and Love Retraining. Proceedings of the International Conference on Learning Representations. [URL] [arXiv] [code]
    [BibTeX]

    @inproceedings{2021_ZimmerSpiegelPokutta_Retrainingpruning,
      year = {2023},
      booktitle = {Proceedings of the International Conference on Learning Representations},
      url = {https://iclr.cc/virtual/2023/poster/10914},
      archiveprefix = {arXiv},
      eprint = {2111.00843},
      primaryclass = {cs.LG},
      author = {Zimmer, Max and Spiegel, Christoph and Pokutta, Sebastian},
      title = {How I Learned to Stop Worrying and Love Retraining},
      code = {https://github.com/ZIB-IOL/BIMP},
      date = {2021-11-01}
    }

11. Chmiela, A., Gleixner, A., Lichocki, P., and Pokutta, S. (2023). Online Learning for Scheduling MIP Heuristics. Proceedings of the International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research, 114–123. DOI: 10.1007/978-3-031-33271-5_8 [arXiv]
    [BibTeX]

    @inproceedings{2023_ChmielaGleixnerLichockiPokutta_Onlinelearningscheduling,
      year = {2023},
      date = {2023-05-23},
      booktitle = {Proceedings of the International Conference on the Integration of Constraint Programming, Artificial Intelligence, and Operations Research},
      pages = {114-123},
      doi = {10.1007/978-3-031-33271-5_8},
      archiveprefix = {arXiv},
      eprint = {2304.03755},
      primaryclass = {math.OC},
      author = {Chmiela, Antonia and Gleixner, Ambros and Lichocki, Pawel and Pokutta, Sebastian},
      title = {Online Learning for Scheduling MIP Heuristics}
    }

12. Mexi, G., Besançon, M., Bolusani, S., Chmiela, A., Hoen, A., and Gleixner, A. (2023, July 7). Scylla: a Matrix-free Fix-propagate-and-project Heuristic for Mixed-integer Optimization. Proceedings of the Conference of the Society for Operations Research in Germany. [arXiv]
    [BibTeX]

    @inproceedings{2023_MexiEtAl_Scyllaheuristic,
      year = {2023},
      booktitle = {Proceedings of the Conference of the Society for Operations Research in Germany},
      archiveprefix = {arXiv},
      eprint = {2307.03466},
      primaryclass = {math.OC},
      author = {Mexi, Gioni and Besançon, Mathieu and Bolusani, Suresh and Chmiela, Antonia and Hoen, Alexander and Gleixner, Ambros},
      title = {Scylla: a Matrix-free Fix-propagate-and-project Heuristic for Mixed-integer Optimization},
      date = {2023-07-07}
    }

13. Thuerck, D., Sofranac, B., Pfetsch, M., and Pokutta, S. (2023, May 20). Learning Cuts Via Enumeration Oracles. Proceedings of the Conference on Neural Information Processing Systems. [arXiv]
    [BibTeX]

    @inproceedings{2023_ThuerckSofranacPfetschPokutta_Learningcutsenumeration,
      year = {2023},
      booktitle = {Proceedings of the Conference on Neural Information Processing Systems},
      archiveprefix = {arXiv},
      eprint = {2305.12197},
      primaryclass = {math.OC},
      author = {Thuerck, Daniel and Sofranac, Boro and Pfetsch, Marc and Pokutta, Sebastian},
      title = {Learning Cuts Via Enumeration Oracles},
      date = {2023-05-20}
    }

14. Macdonald, J., Besançon, M., and Pokutta, S. (2021, October 15). Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings. Proceedings of the International Conference on Machine Learning. [arXiv] [poster] [video]
    [BibTeX]

    @inproceedings{2021_MacdonaldBesanconPokutta_Interpretableneuralnetworks,
      year = {2022},
      booktitle = {Proceedings of the International Conference on Machine Learning},
      archiveprefix = {arXiv},
      eprint = {2110.08105},
      primaryclass = {cs.LG},
      author = {Macdonald, Jan and Besançon, Mathieu and Pokutta, Sebastian},
      title = {Interpretable Neural Networks with Frank-Wolfe: Sparse Relevance Maps and Relevance Orderings},
      poster = {https://pokutta.com/slides/20220712_icml_poster_interpretable_rde.pdf},
      video = {https://slideslive.com/38983588},
      date = {2021-10-15}
    }

15. Tsuji, K., Tanaka, K., and Pokutta, S. (2021, October 4). Pairwise Conditional Gradients without Swap Steps and Sparser Kernel Herding. Proceedings of the International Conference on Machine Learning. [arXiv] [summary] [slides] [code] [video]
    [BibTeX]

    @inproceedings{2021_TsujiTanakaPokutta_Pairwiseconditionalgradients,
      year = {2022},
      booktitle = {Proceedings of the International Conference on Machine Learning},
      archiveprefix = {arXiv},
      eprint = {2110.12650},
      primaryclass = {cond-mat.quant-gas},
      author = {Tsuji, Kazuma and Tanaka, Ken'ichiro and Pokutta, Sebastian},
      title = {Pairwise Conditional Gradients without Swap Steps and Sparser Kernel Herding},
      code = {https://github.com/ZIB-IOL/FrankWolfe.jl},
      slides = {https://pokutta.com/slides/20220624_ICML2022_BPCG.pdf},
      summary = {https://pokutta.com/blog/research/2022/05/21/bpcg-abstract.html},
      video = {https://slideslive.com/38983561},
      date = {2021-10-04}
    }

16. Wäldchen, S., Huber, F., and Pokutta, S. (2022, February 23). Training Characteristic Functions with Reinforcement Learning: XAI-methods Play Connect Four. Proceedings of the International Conference on Machine Learning. [arXiv] [poster] [video]
    [BibTeX]

    @inproceedings{2022_WaeldchenHuberPokutta_CharacteristicfunctionsReinforcementlearning,
      year = {2022},
      booktitle = {Proceedings of the International Conference on Machine Learning},
      archiveprefix = {arXiv},
      eprint = {2202.11797},
      primaryclass = {cs.LG},
      author = {Wäldchen, Stephan and Huber, Felix and Pokutta, Sebastian},
      title = {Training Characteristic Functions with Reinforcement Learning: XAI-methods Play Connect Four},
      poster = {https://pokutta.com/slides/20220712_icml_poster_conn4.pdf},
      video = {https://slideslive.com/38983111},
      date = {2022-02-23}
    }

17. Chmiela, A., Khalil, E. B., Gleixner, A., Lodi, A., and Pokutta, S. (2021). Learning to Schedule Heuristics in Branch-and-bound. Proceedings of the Conference on Neural Information Processing Systems, 34, 24235–24246. [URL] [arXiv] [poster]
    [BibTeX]

    @inproceedings{2021_ChmielaEtAl_Heuristicscheduling,
      year = {2021},
      booktitle = {Proceedings of the Conference on Neural Information Processing Systems},
      month = mar,
      volume = {34},
      pages = {24235–24246},
      url = {https://proceedings.neurips.cc/paper_files/paper/2021/file/cb7c403aa312160380010ee3dd4bfc53-Paper.pdf},
      archiveprefix = {arXiv},
      eprint = {2103.10294},
      primaryclass = {cs.LG},
      author = {Chmiela, Antonia and Khalil, Elias B. and Gleixner, Ambros and Lodi, Andrea and Pokutta, Sebastian},
      title = {Learning to Schedule Heuristics in Branch-and-bound},
      poster = {https://pokutta.com/slides/20211120_poster_NeurIPS21_learningheuristics.pdf},
      date = {2021-03-18}
    }

18. Ziemke, T., Sering, L., Vargas Koch, L., Zimmer, M., Nagel, K., and Skutella, M. (2020). Flows Over Time As Continuous Limits of Packet-based Network Simulations. Proceedings of the EURO Working Group on Transportation Meeting.
    [BibTeX]

    @inproceedings{2021_ZiemkeEtAl_Flowscontinuouslimits:1,
      year = {2020},
      booktitle = {Proceedings of the EURO Working Group on Transportation Meeting},
      author = {Ziemke, Theresa and Sering, Leon and Vargas Koch, Laura and Zimmer, Max and Nagel, Kai and Skutella, Martin},
      title = {Flows Over Time As Continuous Limits of Packet-based Network Simulations}
    }

19. Arumugam, K., Kadampot, I., Tahmasbi, M., Shah, S., Bloch, M., and Pokutta, S. (2017). Modulation Recognition Using Side Information and Hybrid Learning. Proceedings of the IEEE DySPAN.
    [BibTeX]

    @inproceedings{2017_ArumugamKadampotTahmasbiShahBlochPokutta_ModulationRecognition,
      year = {2017},
      booktitle = {Proceedings of the IEEE DySPAN},
      author = {Arumugam, K. and Kadampot, I. and Tahmasbi, M. and Shah, S. and Bloch, M. and Pokutta, Sebastian},
      title = {Modulation Recognition Using Side Information and Hybrid Learning}
    }

20. Roy, A., Xu, H., and Pokutta, S. (2017, June 15). Reinforcement Learning Under Model Mismatch. Proceedings of the Conference on Neural Information Processing Systems. [arXiv]
    [BibTeX]

    @inproceedings{2017_RoyXuPokutta_ReinforcementLearning,
      year = {2017},
      booktitle = {Proceedings of the Conference on Neural Information Processing Systems},
      archiveprefix = {arXiv},
      eprint = {1706.04711},
      primaryclass = {cs.LG},
      author = {Roy, Aurko and Xu, Huan and Pokutta, Sebastian},
      title = {Reinforcement Learning Under Model Mismatch},
      date = {2017-06-15}
    }

Full articles

1. Mundinger, K., Pokutta, S., Spiegel, C., and Zimmer, M. (2024). Extending the Continuum of Six-Colorings. Geombinatorics Quarterly, XXXIV. [URL] [arXiv]
   [BibTeX]

   @article{2024_MundingerPokuttaSpiegelZimmer_SixcoloringsExpansion,
     year = {2024},
     journal = {Geombinatorics Quarterly},
     date = {2024-07-01},
     volume = {XXXIV},
     url = {https://geombina.uccs.edu/past-issues/volume-xxxiv},
     archiveprefix = {arXiv},
     eprint = {2404.05509},
     primaryclass = {math.CO},
     author = {Mundinger, Konrad and Pokutta, Sebastian and Spiegel, Christoph and Zimmer, Max},
     title = {Extending the Continuum of Six-Colorings}
   }

2. Vu‐Han, T. L., Sunkara, V., Bermudez‐Schettino, R., Schwechten, J., Runge, R., Perka, C., Winkler, T., Pokutta, S., Weiß, C., and Pumberger, M. (2024). Feature Engineering for the Prediction of Scoliosis in 5q‐Spinal Muscular Atrophy. Journal of Cachexia, Sarcopenia and Muscle. DOI: 10.1002/jcsm.13599 [URL]
   [BibTeX]

   @article{2024_Pokutta_PredictionScoliosis,
     year = {2024},
     journal = {Journal of Cachexia, Sarcopenia and Muscle},
     date = {2024-12-05},
     doi = {10.1002/jcsm.13599},
     url = {https://onlinelibrary.wiley.com/doi/pdf/10.1002/jcsm.13599},
     author = {Vu‐Han, Tu‐Lan and Sunkara, Vikram and Bermudez‐Schettino, Rodrigo and Schwechten, Jakob and Runge, Robin and Perka, Carsten and Winkler, Tobias and Pokutta, Sebastian and Weiß, Claudia and Pumberger, Matthias},
     title = {Feature Engineering for the Prediction of Scoliosis in 5q‐Spinal Muscular Atrophy}
   }

3. Kevin-Martin, A., Bärmann, A., Braun, K., Liers, F., Pokutta, S., Schneider, O., Sharma, K., and Tschuppik, S. (2023). Data-driven Distributionally Robust Optimization Over Time. INFORMS Journal on Optimization, 5(4), 376–394. DOI: 10.1287/ijoo.2023.0091 [URL] [arXiv]
   [BibTeX]

   @article{2023_KevinEtAl_Datadrivendistributionallyrobust,
     year = {2023},
     journal = {INFORMS Journal on Optimization},
     date = {2023-10-01},
     month = oct,
     volume = {5},
     number = {4},
     pages = {376-394},
     doi = {10.1287/ijoo.2023.0091},
     url = {https://pubsonline.informs.org/doi/pdf/10.1287/ijoo.2023.0091},
     archiveprefix = {arXiv},
     eprint = {2304.05377},
     primaryclass = {math.OC},
     author = {Kevin-Martin, Aigner and Bärmann, Andreas and Braun, Kristin and Liers, Frauke and Pokutta, Sebastian and Schneider, Oskar and Sharma, Kartikey and Tschuppik, Sebastian},
     title = {Data-driven Distributionally Robust Optimization Over Time}
   }

4. Bienstock, D., Muñoz, G., and Pokutta, S. (2023). Principled Deep Neural Network Training Through Linear Programming. Discrete Optimization, 49. DOI: 10.1016/j.disopt.2023.100795 [arXiv] [summary]
   [BibTeX]

   @article{2018_DanielGonzaloPokutta_Polyhedraltraining,
     year = {2023},
     journal = {Discrete Optimization},
     date = {2023-08-01},
     month = aug,
     volume = {49},
     doi = {10.1016/j.disopt.2023.100795},
     archiveprefix = {arXiv},
     eprint = {1810.03218},
     primaryclass = {cs.LG},
     author = {Bienstock, Daniel and Muñoz, Gonzalo and Pokutta, Sebastian},
     title = {Principled Deep Neural Network Training Through Linear Programming},
     summary = {https://www.pokutta.com/blog/research/2018/10/12/DNN-learning-lp-abstract.html}
   }

5. Kruser, J., Sharma, K., Holl, J., and Nohadani, O. (2023). Identifying Patterns of Medical Intervention in Acute Respiratory Failure: A Retrospective Observational Study. Critical Care Explorations.
   [BibTeX]

   @article{2023_KruserSharmaHollNohadani_Medicalinterventionpatterns,
     year = {2023},
     journal = {Critical Care Explorations},
     date = {2023-09-30},
     author = {Kruser, Jacqueline and Sharma, Kartikey and Holl, Jane and Nohadani, Omid},
     title = {Identifying Patterns of Medical Intervention in Acute Respiratory Failure: A Retrospective Observational Study}
   }

6. Kossen, T., Hirzel, M., Madai, V. I., Boenisch, F., Hennemuth, A., Hildebrand, K., Pokutta, S., Sharma, K., Hilbert, A., Sobesky, J., Galinovic, I., Khalil, A. A., Fiebach, J. B., and Frey, D. (2022). Towards Sharing Brain Images: Differentially Private TOF-MRA Images with Segmentation Labels Using Generative Adversarial Networks. Frontiers in Artificial Intelligence. DOI: 10.3389/frai.2022.813842
   [BibTeX]

   @article{2022_KossenEtAl_Brainimagesharing,
     year = {2022},
     journal = {Frontiers in Artificial Intelligence},
     date = {2022-05-02},
     doi = {10.3389/frai.2022.813842},
     author = {Kossen, Tabea and Hirzel, Manuel and Madai, Vince I. and Boenisch, Franziska and Hennemuth, Anja and Hildebrand, Kristian and Pokutta, Sebastian and Sharma, Kartikey and Hilbert, Adam and Sobesky, Jan and Galinovic, Ivana and Khalil, Ahmed A. and Fiebach, Jochen B. and Frey, Dietmar},
     title = {Towards Sharing Brain Images: Differentially Private TOF-MRA Images with Segmentation Labels Using Generative Adversarial Networks}
   }

7. Nohadani, O., and Sharma, K. (2022). Optimization Under Connected Uncertainty. INFORMS Journal on Optimization. DOI: 10.1287/ijoo.2021.0067 [arXiv]
   [BibTeX]

   @article{2022_NohadaniSharma_Connecteduncertainty,
     year = {2022},
     journal = {INFORMS Journal on Optimization},
     date = {2022-01-24},
     doi = {10.1287/ijoo.2021.0067},
     archiveprefix = {arXiv},
     eprint = {2202.10602},
     primaryclass = {math.OC},
     author = {Nohadani, Omid and Sharma, Kartikey},
     title = {Optimization Under Connected Uncertainty}
   }

8. Pokutta, S. (2021). Mathematik, Machine Learning Und Artificial Intelligence. Mitteilungen Der DMV. [URL]
   [BibTeX]

   @article{2021_Pokutta_MathematikMachineLearning,
     year = {2021},
     journal = {Mitteilungen der DMV},
     month = jan,
     url = {https://app.box.com/s/8u6fsucm78e1shyyzoghxar40f7xk6ni},
     author = {Pokutta, Sebastian},
     title = {Mathematik, Machine Learning Und Artificial Intelligence}
   }

9. Ziemke, T., Sering, L., Vargas Koch, L., Zimmer, M., Nagel, K., and Skutella, M. (2021). Flows Over Time As Continuous Limits of Packet-based Network Simulations. Transportation Research Procedia, 52, 123–130. DOI: 10.1016/j.trpro.2021.01.014 [URL]
   [BibTeX]

   @article{2021_ZiemkeEtAl_Flowscontinuouslimits,
     year = {2021},
     journal = {Transportation Research Procedia},
     volume = {52},
     pages = {123-130},
     doi = {10.1016/j.trpro.2021.01.014},
     url = {https://sciencedirect.com/science/article/pii/S2352146521000284},
     author = {Ziemke, Theresa and Sering, Leon and Vargas Koch, Laura and Zimmer, Max and Nagel, Kai and Skutella, Martin},
     title = {Flows Over Time As Continuous Limits of Packet-based Network Simulations}
   }

10. Klus, S., and Gelß, P. (2019). Tensor-based Algorithms for Image Classification. Algorithms, 12(11), 240. DOI: 10.3390/a12110240 [URL] [arXiv]
    [BibTeX]

    @article{2019_KlusGelss_Tensoralgorithmsclassification,
      year = {2019},
      journal = {Algorithms},
      date = {2019-11-09},
      volume = {12},
      number = {11},
      pages = {240},
      doi = {10.3390/a12110240},
      url = {https://mdpi.com/1999-4893/12/11/240},
      archiveprefix = {arXiv},
      eprint = {1910.02150},
      primaryclass = {cs.LG},
      author = {Klus, Stefan and Gelß, Patrick},
      title = {Tensor-based Algorithms for Image Classification}
    }