2 citations · 4 across the 13 of their papers we have counts for
8 papers · 1 filter
Warm-starting active-set solvers using graph neural networks
Ella J. Schmidtobreick, Daniel Arnström, Paul Häusner +1
Quadratic programming (QP) solvers are widely used in real-time control and optimization, but their computational cost often limits applicability in time-critical settings. To reso…
A parallel algorithm for generating Pareto-optimal radiosurgery treatment plans
Joakim da Silva, Daniel Hernández Escobar, Tor Kjellsson Lindblom +2
Using inverse planning tools to create radiotherapy treatment plans is an iterative process, where clinical trade-offs are explored by changing the relative importance of different…
Learning to accelerate distributed ADMM using graph neural networks
Henri Doerks, Paul Häusner, Daniel Hernández Escobar +1
Distributed optimization is fundamental to large-scale machine learning and control applications. Among existing methods, the alternating direction method of multipliers (ADMM) has…
Exploring Modularity of Agentic Systems for Drug Discovery
Laura van Weesep, Samuel Genheden, Ola Engkvist +1
Large-language models (LLMs) and agentic systems present exciting opportunities to accelerate drug discovery. In this study, we examine the modularity of LLM-based agentic systems…
Efficient Image Restoration with State-Dependent Forward Diffusion
Ziwei Luo, Fredrik K. Gustafsson, Jens Sjölund +1
This paper proposes to perform image restoration through a state-dependent mean-reverting forward diffusion (FoD) process. In contrast to traditional diffusion-based approaches tha…
Real-Time Diffusion Policies for Games: Enhancing Consistency Policies with Q-Ensembles
Ruoqi Zhang, Ziwei Luo, Jens Sjölund +3
Diffusion models have shown impressive performance in capturing complex and multi-modal action distributions for game agents, but their slow inference speed prevents practical depl…
Improving Sample Efficiency in Multi-Agent Reinforcement Learning for Simulated Football Games via Exploration
Amir Baghi, Jens Sjölund, Joakim Bergdahl +2
Multi-agent reinforcement learning has shown promise in learning cooperative behaviors in team-based environments. However, such methods often demand extensive training time, which…
Minimal positive Markov realizations
Hamed Taghavian, Jens Sjölund
Finding a positive state-space realization with the minimum dimension for a given transfer function is an open problem in control theory. In this paper, we focus on positive realiz…