Lars Doorenbos

University of Bern

Bern, Switzerland

I am a Ph.D student currently based in Bern, Switzerland, where I work on creating safe and reliable deep learning models through out-of-distribution detection. Before, I completed my Bachelor’s and Master’s degree in Computing Science at the University of Groningen.

news

Apr 7, 2024 Our paper “SuFIA: Language-guided Subtask Autonomy Towards Interactive Robotic Surgical Assistants” has been accepted at the C4SR+ workshop at ICRA 2024
Apr 2, 2024 I have been selected as a DAAD AInet fellow for 2024
Nov 10, 2023 I finished my internship at Nvidia, where I worked on controlling robots with vision-language models
Jul 18, 2023 Our paper “Stochastic Segmentation with Conditional Categorical Diffusion Models” has been accepted at ICCV 2023
Apr 20, 2023 “Generating astronomical spectra from photometry with conditional diffusion models” has been selected as an oral presentation at the Bern Data Science Day 2023

selected publications

2023

  1. Stochastic Segmentation with Conditional Categorical Diffusion Models
    Lukas Zbinden*, Lars Doorenbos*, Theodoros Pissas, and 3 more authors
    International Conference on Computer Vision, 2023
  2. Hyperbolic Random Forests
    Lars Doorenbos, Pablo Márquez-Neila, Raphael Sznitman, and 1 more author
    arXiv preprint arXiv:2308.13279, 2023

2022

  1. Generating astronomical spectra from photometry with conditional diffusion models
    Lars Doorenbos, Stefano Cavuoti, Giuseppe Longo, and 3 more authors
    NeurIPS: Machine Learning for the Physical Sciences Workshop, 2022
  2. Data invariants to understand unsupervised out-of-distribution detection
    Lars Doorenbos, Raphael Sznitman, and Pablo Márquez-Neila
    In European Conference on Computer Vision, 2022