Trajectory Optimisation in Learned Multimodal Dynamical Systems via Latent-ODE Collocation. - Aidan Scannell; Carl Henrik Ek; Arthur Richards (ICRA, 2021)

Mode-constrained Model-based Reinforcement Learning via Gaussian Processes. - Aidan Scannell; Carl Henrik Ek; Arthur Richards (AISTATS, 2023)

Sparse Function-space Representation of Neural Networks. - Aidan Scannell; Riccardo Mereu; Paul E. Chang; Ella Tamir; Joni Pajarinen; Arno Solin (CoRR, 2023)

Function-space Parameterization of Neural Networks for Sequential Learning. - Aidan Scannell; Riccardo Mereu; Paul Edmund Chang; Ella Tamir; Joni Pajarinen; Arno Solin (ICLR, 2024)

Residual learning and context encoding for adaptive offline-to-online reinforcement learning. - Mohammadreza Nakhaei; Aidan Scannell; Joni Pajarinen (L4DC, 2024)

iQRL - Implicitly Quantized Representations for Sample-efficient Reinforcement Learning. - Aidan Scannell; Kalle Kujanpää; Yi Zhao 014; Mohammadreza Nakhaei; Arno Solin; Joni Pajarinen (CoRR, 2024)

Entropy Regularized Task Representation Learning for Offline Meta-Reinforcement Learning. - Mohammadreza Nakhaeinezhadfard; Aidan Scannell; Joni Pajarinen (AAAI, 2025)

Discrete Codebook World Models for Continuous Control. - Aidan Scannell; Mohammadreza Nakhaeinezhadfard; Kalle Kujanpää; Yi Zhao 014; Kevin Sebastian Luck; Arno Solin; Joni Pajarinen (ICLR, 2025)

Generalist World Model Pre-Training for Efficient Reinforcement Learning. - Yi Zhao 014; Aidan Scannell; Yuxin Hou; Tianyu Cui; Le Chen; Dieter Büchler; Arno Solin; Juho Kannala; Joni Pajarinen (CoRR, 2025)