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 (* equal contribution)

Conference on Robot Learning (CoRL) 2024

[Paper] [Website]

Leveraging Unlabeled Offline Data via Model-based Active Semi-supervised Reinforcement Learning

Yi Zhao, Aidan Scannell, Tianyu Cui, Le Chen, Dieter Büchler, Arno Solin, Juho Kannala, Joni Pajarinen

Under review, preprint to appear soon 2024

Bi-Level Motion Imitation for Humanoid Robots

Wenshuai Zhao, Yi Zhao, Joni Pajarinen, Michael Muehlebach

Conference on Robot Learning (CoRL) 2024

iQRL--Implicitly Quantized Representations for Sample-efficient Reinforcement Learning

Aidan Scannell, Kalle Kujanpää, Yi Zhao, Mohammadreza Nakhaei, Arno Solin, Joni Pajarinen

International Conference on Machine Learning, Workshop (ICML Workshop) 2024

[Paper]

Optimistic Multi-Agent Policy Gradient

Wenshuai Zhao, Yi Zhao, Zhiyuan Li, Juho Kannala, Joni Pajarinen

International Conference on Machine Learning (ICML) 2024

[Paper] [Code] [Website]

Hscnet++: Hierarchical Scene Coordinate Classification and Regression for Visual Localization with Transformer

Shuzhe Wang, Zakaria Laskar, Iaroslav Melekhov, Xiaotian Li, Yi Zhao, Giorgos Tolias, Juho Kannala

International Journal of Computer Vision (IJCV) 2024

[Paper]

Continuous Monte Carlo Graph Search

Kalle Kujanpää*, Amin Babadi*, Yi Zhao, Juho Kannala, Alexander Ilin, Joni Pajarinen (* equal contribution)

International Conference on Autonomous Agents and Multiagent Systems (AAMAS) 2023

[Paper]

Simplified Temporal Consistency Reinforcement Learning

Yi Zhao, Wenshuai Zhao, Rinu Boney, Juho Kannala, Joni Pajarinen

International Conference on Machine Learning (ICML) 2023

[Paper] [Code]

Adaptive Behavior Cloning Regularization for Stable Offline-to-Online Reinforcement Learning

Yi Zhao*, Rinu Boney*, Alexander Ilin, Juho Kannala, Joni Pajarinen (* equal contribution)

European Symposium on Artificial Neural Networks, Computational Intelligence and Machine Learning 2022

[Paper] [Code]

Learning to drive (l2d) as a low-cost benchmark for real-world reinforcement learning

Ari Viitala*, Rinu Boney*, Yi Zhao, Alexander Ilin, Juho Kannala (* equal contribution)

International Conference on Advanced Robotics 2021

[Paper] [Website]

Hierarchical scene coordinate classification and regression for visual localization

Xiaotian Li, Shuzhe Wang, Yi Zhao, Jakob Verbeek, Juho Kannala

Conference on Computer Vision and Pattern Recognition (CVPR) 2020

[Paper] [Code]