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Aidan Scannell
Aidan Scannell
Finnish Centre for Artificial Intelligence, Aalto University
Verified email at aalto.fi - Homepage
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Cited by
Year
Trajectory optimisation in learned multimodal dynamical systems via latent-ode collocation
A Scannell, CH Ek, A Richards
2021 IEEE International Conference on Robotics and Automation (ICRA), 12745 …, 2021
102021
Sparse Function-space Representation of Neural Networks
A Scannell, R Mereu, P Chang, E Tamir, J Pajarinen, A Solin
ICML 2023 Workshop on Duality Principles for Modern Machine Learning, 2023
42023
Function-space Parameterization of Neural Networks for Sequential Learning
A Scannell, R Mereu, PE Chang, E Tamir, J Pajarinen, A Solin
The Twelfth International Conference on Learning Representations, 2024
32024
iQRL--Implicitly Quantized Representations for Sample-efficient Reinforcement Learning
A Scannell, K Kujanpää, Y Zhao, M Nakhaei, A Solin, J Pajarinen
arXiv preprint arXiv:2406.02696, 2024
12024
Mode-constrained Model-based Reinforcement Learning via Gaussian Processes
A Scannell, CH Ek, A Richards
International Conference on Artificial Intelligence and Statistics, 3299-3314, 2023
12023
Bayesian Learning for Control in Multimodal Dynamical Systems
A Scannell
University of Bristol, 2022
12022
Residual Learning and Context Encoding for Adaptive Offline-to-Online Reinforcement Learning
M Nakhaei, A Scannell, J Pajarinen
Proceedings of the 6th Annual Learning for Dynamics & Control Conference 242 …, 2024
2024
Quantized Representations Prevent Dimensional Collapse in Self-predictive RL
A Scannell, K Kujanpää, Y Zhao, M Nakhaeinezhadfard, A Solin, ...
ICML 2024 Workshop: Aligning Reinforcement Learning Experimentalists and …, 0
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