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2020 – today
- 2024
[c4]Aidan Scannell, Riccardo Mereu, Paul Edmund Chang, Ella Tamir, Joni Pajarinen, Arno Solin:
Function-space Parameterization of Neural Networks for Sequential Learning. ICLR 2024- [c3]Mohammadreza Nakhaei, Aidan Scannell, Joni Pajarinen:
Residual learning and context encoding for adaptive offline-to-online reinforcement learning. L4DC 2024: 1107-1121 - [i4]Aidan Scannell, Riccardo Mereu, Paul E. Chang, Ella Tamir, Joni Pajarinen, Arno Solin:
Function-space Parameterization of Neural Networks for Sequential Learning. CoRR abs/2403.10929 (2024) - [i3]Aidan Scannell, Kalle Kujanpää, Yi Zhao, Mohammadreza Nakhaei, Arno Solin, Joni Pajarinen:
iQRL - Implicitly Quantized Representations for Sample-efficient Reinforcement Learning. CoRR abs/2406.02696 (2024) - [i2]Mohammadreza Nakhaei, Aidan Scannell, Joni Pajarinen:
Residual Learning and Context Encoding for Adaptive Offline-to-Online Reinforcement Learning. CoRR abs/2406.08238 (2024) - 2023
- [c2]Aidan Scannell, Carl Henrik Ek, Arthur Richards:
Mode-constrained Model-based Reinforcement Learning via Gaussian Processes. AISTATS 2023: 3299-3314 - [i1]Aidan Scannell
, Riccardo Mereu, Paul E. Chang, Ella Tamir, Joni Pajarinen, Arno Solin:
Sparse Function-space Representation of Neural Networks. CoRR abs/2309.02195 (2023) - 2021
- [c1]Aidan Scannell, Carl Henrik Ek, Arthur Richards:
Trajectory Optimisation in Learned Multimodal Dynamical Systems via Latent-ODE Collocation. ICRA 2021: 12745-12751
Coauthor Index
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