Publications

Yi Zhao, Aidan Scannell, Cui Yuxin, Tianyu Cui, Le Chen, Arno Solin, Juho Kannala, Joni Pajarinen (2025). Generalist World Model Pre-Training for Efficient Reinforcement Learning. arXiv preprint arXiv:2502.19544.

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Aidan Scannell, Mohammadreza Nakhaei, Kalle Kujanpää, Yi Zhao, Kevin Luck, Arno Solin, Joni Pajarinen (2025). Discrete Codebook World Models for Continuous Control. The Thirteenth International Conference on Learning Representations (ICLR).

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Mohammadreza Nakhaei, Aidan Scannell, Joni Pajarinen (2025). Entropy Regularized Task Representation Learning for Offline Meta-Reinforcement Learning. Proceedings of the AAAI Conference on Artificial Intelligence.

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Aidan Scannell, Kalle Kujanpää, Yi Zhao, Mohammadreza Nakhaei, Arno Solin, Joni Pajarinen (2024). iQRL - Implicitly Quantized Representations for Sample-efficient Reinforcement Learning. arXiv preprint arXiv:2406.02696.

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Aidan Scannell, Kalle Kujanpää, Yi Zhao, Mohammadreza Nakhaei, Arno Solin, Joni Pajarinen (2024). Quantized Representations Prevent Dimensional Collapse in Self-predictive RL. ICML Workshop on Aligning Reinforcement Learning Experimentalists and Theorists (ARLET).

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Mohammadreza Nakhaei, Aidan Scannell, Joni Pajarinen (2024). Residual Learning and Context Encoding for Adaptive Offline-to-Online Reinforcement Learning. 4th Annual Conference on Learning for Dynamics and Control (L4DC).

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Aidan Scannell, Riccardo Mereu, Paul Chang, Ella Tamir, Joni Pajarinen, Arno Solin (2024). Function-space Parameterization of Neural Networks for Sequential Learning. The Twelth International Conference on Learning Representations (ICLR).

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Aidan Scannell, Riccardo Mereu, Paul Chang, Ella Tamir, Joni Pajarinen, Arno Solin (2023). Sparse Function-space Representation of Neural Networks. ICML 2023 Workshop on Duality Principles for Modern Machine Learning.

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Aidan Scannell, Carl Henrik Ek, Arthur Richards (2023). Mode-constrained Model-based Reinforcement Learning via Gaussian Processes. 26th International Conference on Artificial Intelligence and Statistics (AISTATS).

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Aidan Scannell (2022). Bayesian Learning for Control in Multimodal Dynamical Systems. University of Bristol.

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Aidan Scannell, Carl Henrik Ek, Arthur Richards (2021). Identifiable Mixtures of Sparse Variational Gaussian Process Experts. UK RAS CDT Conference.

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Aidan Scannell, Carl Henrik Ek, Arthur Richards (2021). Trajectory Optimisation in Learned Multimodal Dynamical Systems via Latent-ODE Collocation. IEEE International Conference on Robotics and Automation (ICRA).

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