September 24, 2025

1. Oleksii Molodchyk (Hamburg University of Technology, Germany)
    Kernel Regression Meets System Identification

2. Johannes Müller (TU Berlin, Germany)
    Optimal Rates of Convergence for Entropy Regularization in Discounted Markov Decision Processes

3. Paul Navas (TU Dortmund, Germany)
    A Hilbert statistical manifold based on the Sinkhorn divergence

4. Hoang Khang Nguyen (University of California Los Angeles, United States)
    Revisiting Over-smoothing and Over-squashing Using Ollivier-Ricci Curvature

5. Oskar Nordenfors (Umeå University, Sweden)
    Neural Network Ensembles Provably Learn Symmetries

6. Elias Nyholm (Chalmers University of Technology, Sweden)
    Unifying Transformers and Convolutional Networks as Equivariant Maps

7. Guanru Pan (Hamburg University of Technology, Germany)
    Data-driven stochastic modeling and prediction with residual disturbance

8. Moritz Piening (TU Berlin, Germany)
    Slicing the Gaussian Mixture Wasserstein Distance

9. Md Ashfaqur Rahman (University of Arkansas at Little Rock, United States)

10. Konstantin Riedl (University of Oxford, United Kingdom)
      Convergence Analysis of Nonlinear Parabolic PDE Models with Neural Network Terms Trained with Gradient Descent

11. Tim Roith (DESY, Germany)
      Gullible networks and the mathematics of adversarial attacks

12. Daniel Ruprecht (Hamburg University of Technology, Germany)
      Neural operators as coarse models for parallel-in-time integration methods

13. Melanie Schaller (Institut für Informationsverarbeitung, Germany)
      ModeConv: A Novel Convolution for Distinguishing Anomalous and Normal Structural Behavior

14. Darius Schaub (University Medical Center Hamburg-Eppendorf, Germany)
      2D Tissue reassembly with E(2)-equivariant graph neural cellular automata

15. Lucas Schmitt (Julius-Maximilians-Universität Würzburg, Germany)
      Adversarial Training as a Primal-Dual Problem

16. Henning Schwarz (Hamburg University of Technology, Germany)
      Convolutional Autoencoder based Prediction of Ditching Loads with Disentangled Latent Space

17. Sebastian Scott (University of Würzburg, Germany)
      On Optimal regularisation parameters via bilevel learning

18. Mariia Seleznova (LMU Munich, Germany)
      Neural Tangent Kernel Alignment as a Lens on Trained Neural Networks

19. Pradeep Kumar Sharma (University of Delhi, India)
      Stackelberg games for federated learning

20. Zakhar Shumaylov (University of Cambridge, United Kingdom)
      Lie Algebra Canonicalization: Equivariant Neural Operators under arbitrary Lie Groups

21. Rishi Sonthalia (Boston College, United States)
      Identification of Mean-Field Dynamics using Transformers

22. Martin Spindler (University of Hamburg, Germany)
      DoubleMLDeep: Estimation of Causal Effects with Multimodal Data

23. Maximilian Steffen (Karlsruhe Institute of Technology, Germany)
      Statistical guarantees for stochastic Metropolis-Hastings

24. Florin Suciu (Université Paris Dauphine-PSL, France)
      Motion planning, rough controls, and deep neural networks

25. Diaaeldin Taha (Max Planck Institute for Mathematics in the Sciences, Germany)
      Demystifying Topological Message-Passing with Relational Structures: A Case Study on Oversquashing in Simplicial Message-Passing

26. Mahsa Taheri (University of Hamburg, Germany)
      Regularization can make diffusion models more efficient

27. Alessandro Tamai (SISSA, Italy)
      Testing the Algebraicity Hypothesis

28. Johanna Tengler (University of Twente, Netherlands)
      Manifold limit for the training of shallow graph convolutional neural networks

29. Lucia Testa (University Medical Center Hamburg Eppendorf, Germany)
      Stability of graph convolutional networks under small random topology perturbations

30. Nicolás Valenzuela (University of Chile, Chile)
      Bounds on the approximation error for deep neural networks applied to dispersive models: nonlinear waves

31. Antonis Vasileiou (RWTH Aachen University, Germany)
      Covered Forest: Fine-grained generalization analysis of graph neural networks

32. Viktor Vigren Näslund (Umeå University, Sweden)
      Extending neural ODEs to encoder-decoder architectures via compressing vector fields

33. Lukas Weigand (Helmholtz Imaging, Germany)
      A gradient flow interpretation of Adversarial Attacks

34. Tak Ming Wong (Helmholtz-Zentrum Hereon, Germany)
      Self-supervised and physics-informed generative networks for the phase retrieval problem

35. Zusen Xu (Weierstrass Institute, Germany)
      Wasserstein Fisher-Rao Proximal Sampler

36. Hossein Zakerinia (Institute of Science and Technology Austria, Austria)
      Deep Multi-Task Learning Has Low Amortized Intrinsic Dimensionality

37. Konstantin Zörner (Hamburg University of Technology, Germany)
      Improving Computational Hypergraph Discovery through Gaussian Process-Based Parameter Optimization

38. Giulio Zucal (Max Planck Institute of Molecular Cell Biology and Genetics, Germany)
      Graph and Hypergraph limits: new tools for Machine Learning