🔄 Updated Arxiv Paper Title: Learning to accelerate distributed ADMM using graph neural networks Authors: Henri Doerks, Paul H\"ausner, Daniel Hern\'andez Escobar, Jens Sj\"olund Read more: https://arxiv.org/abs/2509.05288

I’m happy to share that I’ll be spending the fall semester at Princeton as a visiting student in the Department of Operations Research and Financial Engineering (ORFE), working with @stellato.io funded through the WASP program. If you’re in the area and would like to connect, feel free to reach out.

Would you present your next NeurIPS paper in Europe instead of traveling to San Diego (US) if this was an option? Søren Hauberg (DTU) and I would love to hear the answer through this poll: (1/6)

This week, we had the pleasure of hosting Sweden’s first @logconference.bsky.social meetup at Uppsala University! Over two days, we brought together researchers and industry professionals working at the intersection of machine learning, graphs, and geometry.

Hej 🦋! I’m happy to share that our latest TMLR paper that uses graph neural networks to learn incomplete factorization preconditioners for the conjugate gradient method has been accepted as an oral presentation at next week’s Learning on Graphs (LoG) conference! openreview.net/forum?id=Foz...