Publications and Talks

Submitted Articles

  1. Preparing for Rubin-LSST -- Detecting Brightest Cluster Galaxies with Machine Learning in the LSST DP0.2 simulation
    A. Chu, L. Doeser, S. Ding, J. Jasche
    [https://arxiv.org/abs/2503.15945] (citations: 0)

  2. Learning the Universe: Learning to Optimize Cosmic Initial Conditions with Non-Differentiable Structure Formation Models
    L. Doeser, M. Ata, J. Jasche
    [https://www.arxiv.org/abs/2502.13243] (citations: 3)

  3. Learning the Universe: 3 Gpc/h Tests of a Field Level N-body Simulation Emulator
    M.T. Scoggins, M. Ho, F. Villaescusa-Navarro, D. Jamieson, L. Doeser, G.L. Bryan
    [https://arxiv.org/abs/2409.02154] (citations: 1)

  4. COmoving Computer Acceleration (COCA): N-body simulations in an emulated frame of reference
    D. Bartlett, L. Doeser, M. Chiarenza, F. Leclercq
    [https://arxiv.org/abs/2409.02154] (citations: 6)

  5. Bayesian Inference of Initial Conditions from Non-Linear Cosmic Structures using Field-Level Emulators
    L. Doeser, D. Jamieson, S. Stopyra, G. Lavaux, F. Leclercq, J. Jasche
    [https://arxiv.org/abs/2312.09271] (citations: 27)

Conference Proceedings

  1. Invariant Sets for Integrators and Quadrotor Obstacle Avoidance
    L. Doeser, P. Nilsson, A. D. Ames, R. M. Murray
    Proceedings of the American Control Conference 2020, Denver, 1-3 July 2020. Publisher: IEEE [https://ieeexplore.ieee.org/abstract/document/9147872] (citations: 12)

Theses

  1. A Machine Learning Approach for Comprehending Cosmic Expansion
    L. Doeser
    Master Thesis in Engineering Physics (track: Theoretical Physics), KTH Royal Institute of Technology
    [https://kth.diva-portal.org/]

  2. Coupling of Light Into a Silicon-on-Silica Strip Waveguide
    L. Doeser, E. Rydving
    Bachelor Thesis in Engineering Physics, KTH Royal Institute of Technology
    [https://kth.diva-portal.org/]

Talks

  1. Learning the Universe by Learning to Optimize Cosmic Initial Conditions with Non-Differentiable Simulators
    Conference: AI for Science Symposium, Royal Swedish Academy of Sciences, Stockholm, Sweden Sep, 2025
  2. The light revealing our Universe
    Workshop: Tom Tits Experiment Science Center, Stockholm, Sweden Aug, 2025
  3. Learning to Optimize Cosmic Initial Conditions with Non-Differentiable Structure Formation Models
    Conference: European Coalition for AI in Fundamental Physics, Sardinia, Italy June, 2025
  4. Accelerating cosmological field-level inference deep learning
    Seminar: Statistics and Machine Learning, Princeton University, USA March, 2025
  5. Accelerating cosmological simulations and statistical inference with machine learning
    OKC x Industry, Savantic AB HQ, Stockholm, Sweden February, 2025
  6. Bayesian Inference of Initial Conditions from Non-Linear Cosmic Structures using Field-Level Emulators
    Working Group Meeting: Oskar Klein Centre, Cosmology and Gravity WG, Stockholm, Sweden October, 2024
  7. Bayesian Inference of Initial Conditions from Non-Linear Cosmic Structures using Field-Level Emulators
    Conference: New Strategies for Extracting Information from Galaxy Surveys II, Sexten/Sesto, Italy July, 2024
  8. Towards Robust Bayesian inference (ROBIN) using physics-informed priors from cosmological simulations
    Conference: COSMO 2021 (Statistical Challenges for 21st Century Cosmology), Chania, Crete, Greece May, 2024
  9. Bayesian Inference of Initial Conditions from Non-Linear Cosmic Structures using Field-Level Emulators
    Virtual Seminar: USM Galaxies and Lensing Seminar, Munich, Germany May, 2024
  10. Bayesian Inference of Initial Conditions from Non-Linear Cosmic Structures using Field-Level Emulators
    Virtual Seminar: Astrophysics Group, Imperial College London, UK January, 2024
  11. Bayesian Inference of Initial Conditions from Non-Linear Cosmic Structures using Field-Level Emulators
    Conference: Debating the Potential of Machine Learning in Astronomical Surveys #2, ML-IAP/CCA 2023, Paris, France November, 2023
  12. Field-level Emulator in BORG
    Collaboration Meeting: Simons Foundation, Learning the Universe, New York, USA September, 2023
  13. Machine Learning the Initial Conditions of the Universe within BORG
    Cosmology Lunch Talk: Oskar Klein Centre, Stockholm University, Sweden May, 2023