65 citations · 149 across the 17 of their papers we have counts for
6 papers · 1 filter
A Grid-Structured Model of Tubular Reactors
Katsiaryna Haitsiukevich, Samuli Bergman, Cesar de Araujo Filho +2
We propose a grid-like computational model of tubular reactors. The architecture is inspired by the computations performed by solvers of partial differential equations which descri…
Automating Privilege Escalation with Deep Reinforcement Learning
Kalle Kujanpää, Willie Victor, Alexander Ilin
AI-based defensive solutions are necessary to defend networks and information assets against intelligent automated attacks. Gathering enough realistic data for training machine lea…
Learning to Assist Agents by Observing Them
Antti Keurulainen, Isak Westerlund, Samuel Kaski +1
The ability of an AI agent to assist other agents, such as humans, is an important and challenging goal, which requires the assisting agent to reason about the behavior and infer t…
Behaviour-conditioned policies for cooperative reinforcement learning tasks
Antti Keurulainen, Isak Westerlund, Ariel Kwiatkowski +2
The cooperation among AI systems, and between AI systems and humans is becoming increasingly important. In various real-world tasks, an agent needs to cooperate with unknown partne…
SANSformers: Self-Supervised Forecasting in Electronic Health Records with Attention-Free Models
Yogesh Kumar, Alexander Ilin, Henri Salo +3
Despite the proven effectiveness of Transformer neural networks across multiple domains, their performance with Electronic Health Records (EHR) can be nuanced. The unique, multidim…
Learning of feature points without additional supervision improves reinforcement learning from images
Rinu Boney, Alexander Ilin, Juho Kannala
In many control problems that include vision, optimal controls can be inferred from the location of the objects in the scene. This information can be represented using feature poin…