19 citations · 41 across the 6 of their papers we have counts for
6 papers
TransFusion: Generating Long, High Fidelity Time Series using Diffusion Models with Transformers
Md Fahim Sikder, Resmi Ramachandranpillai, Fredrik Heintz
The generation of high-quality, long-sequenced time-series data is essential due to its wide range of applications. In the past, standalone Recurrent and Convolutional Neural Netwo…
Achieving a Data-driven Risk Assessment Methodology for Ethical AI
Anna Felländer, Jonathan Rebane, Stefan Larsson +2
The AI landscape demands a broad set of legal, ethical, and societal considerations to be accounted for in order to develop ethical AI (eAI) solutions which sustain human values an…
Scalar reward is not enough: A response to Silver, Singh, Precup and Sutton (2021)
Peter Vamplew, Benjamin J. Smith, Johan Kallstrom +9
The recent paper `"Reward is Enough" by Silver, Singh, Precup and Sutton posits that the concept of reward maximisation is sufficient to underpin all intelligence, both natural and…
Towards Utilitarian Combinatorial Assignment with Deep Neural Networks and Heuristic Algorithms
Fredrik Präntare, Mattias Tiger, David Bergström +2
This paper presents preliminary work on using deep neural networks to guide general-purpose heuristic algorithms for performing utilitarian combinatorial assignment. In more detail…
A Practical Guide to Multi-Objective Reinforcement Learning and Planning
Conor F. Hayes, Roxana Rădulescu, Eugenio Bargiacchi +15
Real-world decision-making tasks are generally complex, requiring trade-offs between multiple, often conflicting, objectives. Despite this, the majority of research in reinforcemen…
Enhancing Lattice-based Motion Planning with Introspective Learning and Reasoning
Mattias Tiger, David Bergström, Andreas Norrstig +1
Lattice-based motion planning is a hybrid planning method where a plan made up of discrete actions simultaneously is a physically feasible trajectory. The planning takes both discr…