3 papers
cs.LG2026
Fine-tuning Pocket-Aware Diffusion Models via Denoising Policy Optimization
Yuan Xue, Daniel Kudenko, Megha Khosla
Structure-based drug design has been accelerated by pocket-aware 3D generative models, yet most methods primarily fit the training distribution and may fall short of satisfying mul…
cs.NI2025
Sustainable broadcasting in Blockchain Networks with Reinforcement Learning
Danila Valko, Daniel Kudenko
Recent estimates put the carbon footprint of Bitcoin and Ethereum at an average of 64 and 26 million tonnes of CO2 per year, respectively. To address this growing problem, several…
cs.LG2025
Improving the Effectiveness of Potential-Based Reward Shaping in Reinforcement Learning
Henrik Müller, Daniel Kudenko
Potential-based reward shaping is commonly used to incorporate prior knowledge of how to solve the task into reinforcement learning because it can formally guarantee policy invaria…