Pajarinen, Joni

38 publications

AAAI 2025 AgentMixer: Multi-Agent Correlated Policy Factorization Zhiyuan Li, Wenshuai Zhao, Lijun Wu, Joni Pajarinen

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

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

CoRL 2025 Extracting Visual Plans from Unlabeled Videos via Symbolic Guidance Wenyan Yang, Ahmet Tikna, Yi Zhao, Yuying Zhang, Luigi Palopoli, Marco Roveri, Joni Pajarinen

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

ECML-PKDD 2025 Grouped Discrete Representation for Object-Centric Learning Rongzhen Zhao, Vivienne Wang, Juho Kannala, Joni Pajarinen

ICML 2025 Hierarchical Reinforcement Learning with Uncertainty-Guided Diffusional Subgoals Vivienne Huiling Wang, Tinghuai Wang, Joni Pajarinen

ICML 2025 Learning Progress Driven Multi-Agent Curriculum Wenshuai Zhao, Zhiyuan Li, Joni Pajarinen

NeurIPS 2025 MetaSlot: Break Through the Fixed Number of Slots in Object-Centric Learning Hongjia Liu, Rongzhen Zhao, Haohan Chen, Joni Pajarinen

ICML 2025 Monte-Carlo Tree Search with Uncertainty Propagation via Optimal Transport Tuan Quang Dam, Pascal Stenger, Lukas Schneider, Joni Pajarinen, Carlo D’Eramo, Odalric-Ambrym Maillard

ICLR 2025 Multi-Scale Fusion for Object Representation Rongzhen Zhao, Vivienne Huiling Wang, Juho Kannala, Joni Pajarinen

JAIR 2024 A Unified Perspective on Value Backup and Exploration in Monte-Carlo Tree Search Tuan Dam, Carlo D'Eramo, Jan Peters, Joni Pajarinen

AAAI 2024 Backpropagation Through Agents Zhiyuan Li, Wenshuai Zhao, Lijun Wu, Joni Pajarinen

CoRL 2024 Bi-Level Motion Imitation for Humanoid Robots Wenshuai Zhao, Yi Zhao, Joni Pajarinen, Michael Muehlebach

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

ICML 2024 Optimistic Multi-Agent Policy Gradient Wenshuai Zhao, Yi Zhao, Zhiyuan Li, Juho Kannala, Joni Pajarinen

ICML 2024 Probabilistic Subgoal Representations for Hierarchical Reinforcement Learning Vivienne Huiling Wang, Tinghuai Wang, Wenyan Yang, Joni-Kristian Kamarainen, Joni Pajarinen

ICMLW 2024 Quantized Representations Prevent Dimensional Collapse in Self-Predictive RL Aidan Scannell, Kalle Kujanpää, Yi Zhao, Mohammadreza Nakhaeinezhadfard, Arno Solin, Joni Pajarinen

CoRL 2024 RP1M: A Large-Scale Motion Dataset for Piano Playing with Bi-Manual Dexterous Robot Hands Yi Zhao, Le Chen, Jan Schneider, Quankai Gao, Juho Kannala, Bernhard Schölkopf, Joni Pajarinen, Dieter Büchler

L4DC 2024 Residual Learning and Context Encoding for Adaptive Offline-to-Online Reinforcement Learning Mohammadreza Nakhaei, Aidan Scannell, Joni Pajarinen

ICML 2023 Hierarchical Imitation Learning with Vector Quantized Models Kalle Kujanpää, Joni Pajarinen, Alexander Ilin

ICLRW 2023 Prioritized Offline Goal-Swapping Experience Replay Wenyan Yang, Joni Pajarinen, Dingding Cai, Joni-kristian Kamarainen

ICML 2023 Simplified Temporal Consistency Reinforcement Learning Yi Zhao, Wenshuai Zhao, Rinu Boney, Juho Kannala, Joni Pajarinen

AAAI 2023 State-Conditioned Adversarial Subgoal Generation Vivienne Huiling Wang, Joni Pajarinen, Tinghuai Wang, Joni-Kristian Kämäräinen

ICLR 2022 Boosted Curriculum Reinforcement Learning Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen

NeurIPSW 2022 Constrained Imitation Q-Learning with Earth Mover’s Distance Reward Wenyan Yang, Nataliya Strokina, Joni Pajarinen, Joni-kristian Kamarainen

ICML 2022 Curriculum Reinforcement Learning via Constrained Optimal Transport Pascal Klink, Haoyi Yang, Carlo D’Eramo, Jan Peters, Joni Pajarinen

ICLR 2022 Topological Experience Replay Zhang-Wei Hong, Tao Chen, Yen-Chen Lin, Joni Pajarinen, Pulkit Agrawal

AISTATS 2021 Latent Derivative Bayesian Last Layer Networks Joe Watson, Jihao Andreas Lin, Pascal Klink, Joni Pajarinen, Jan Peters

JMLR 2021 A Probabilistic Interpretation of Self-Paced Learning with Applications to Reinforcement Learning Pascal Klink, Hany Abdulsamad, Boris Belousov, Carlo D'Eramo, Jan Peters, Joni Pajarinen

ICML 2021 Convex Regularization in Monte-Carlo Tree Search Tuan Q Dam, Carlo D’Eramo, Jan Peters, Joni Pajarinen

IJCAI 2020 Generalized Mean Estimation in Monte-Carlo Tree Search Tuan Dam, Pascal Klink, Carlo D'Eramo, Jan Peters, Joni Pajarinen

MLJ 2019 Compatible Natural Gradient Policy Search Joni Pajarinen, Hong Linh Thai, Riad Akrour, Jan Peters, Gerhard Neumann

ICML 2019 Projections for Approximate Policy Iteration Algorithms Riad Akrour, Joni Pajarinen, Jan Peters, Gerhard Neumann

AAAI 2016 Sparse Latent Space Policy Search Kevin Sebastian Luck, Joni Pajarinen, Erik Berger, Ville Kyrki, Heni Ben Amor

ECML-PKDD 2013 Expectation Maximization for Average Reward Decentralized POMDPs Joni Pajarinen, Jaakko Peltonen

IJCAI 2011 Efficient Planning for Factored Infinite-Horizon DEC-POMDPs Joni Pajarinen, Jaakko Peltonen

ECML-PKDD 2010 Efficient Planning in Large POMDPs Through Policy Graph Based Factorized Approximations Joni Pajarinen, Jaakko Peltonen, Ari Hottinen, Mikko A. Uusitalo