Publications

Publications of the NEITALG project, sorted by year.

Publications

2026

  1. Ensemble optimal control for managing drug resistance in cancer therapies
    Alessandro Scagliotti, Federico Scagliotti, Laura Deborah Locati, and Federico Sottotetti
    Bulletin of Mathematical Biology, 2026
  2. Constrained consensus-based optimization and numerical heuristics for the few particle regime
    Jonas Beddrich, Enis Chenchene, Massimo Fornasier, Hui Huang, and Barbara Wohlmuth
    Journal of Global Optimization, 2026

Preprints

2026

  1. Trade-off invariance for weighted scalarizations in multi-objective optimization
    Jona Klemenc and Alessandro Scagliotti
    2026
    arXiv
  2. Approximation in Metric Sobolev Spaces: A General Framework
    Massimo Fornasier and Giacomo Enrico Sodini
    2026
    arXiv
  3. Sharp Rates of MMD Empirical Estimation with Power Kernels
    Francesco Colasanto, Matteo Focardi, Massimo Fornasier, and Francesco Mattesini
    2026
    arXiv
  4. Quantifying Concentration Phenomena of Mean-Field Transformers in the Low-Temperature Regime
    Albert Alcalde, Leon Bungert, Konstantin Riedl, and Tim Roith
    2026
    arXiv
  5. From consensus-based optimization to evolution strategies: Proof of global convergence
    Massimo Fornasier, Hui Huang, Jona Klemenc, and Greta Malaspina
    2026
    arXiv
  6. SympFormer: Accelerated attention blocks via Inertial Dynamics on Density Manifolds
    Viktor Stein, Wuchen Li, and Gabriele Steidl
    2026
    arXiv
  7. Approximating f-Divergences with Rank Statistics
    Viktor Stein and José Manuel Frutos
    2026
    arXiv
  8. Well-Posed KL-Regularized Control via Wasserstein and Kalman-Wasserstein KL Divergences
    Viktor Stein, Adwait Datar, and Nihat Ay
    2026
    arXiv
  9. Risk-Averse Ensemble Control for Control-Affine Systems
    Alessandro Scagliotti and Thomas M Surowiec
    2026
    arXiv
  10. On the Concavity of Tsallis Entropy along the Heat Flow
    Lukang Sun
    2026
    arXiv
  11. Concentration for random Euclidean combinatorial optimization
    Matteo d’Achille, Francesco Mattesini, and Dario Trevisan
    2026
    arXiv
  12. Adapted Wasserstein Barycenters of Gaussian Processes
    Madhu Gunasingam, Francesco Mattesini, Johannes Wiesel, and Ting-Kam Leonard Wong
    2026
    arXiv
  13. Statistical Learning Theory for Distributional Classification
    Christian Fiedler
    2026
    arXiv

2025

  1. Position-Blind Ptychography: Viability of image reconstruction via data-driven variational inference
    Simon Welker, Lorenz Kuger, Tim Roith, Berthy Feng, Martin Burger, Timo Gerkmann, and Henry Chapman
    2025
    arXiv