Maximilian Igl

40 papers A* 13A 2Misc 1Journal 20Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Closed-Loop Supervised Fine-Tuning of Tokenized Traffic Models. CVPR Zhejun Zhang, Péter Karkus, Maximilian Igl, Wenhao Ding, Yuxiao Chen, Boris Ivanovic, Marco Pavone
2025	A*	`conf`	Gen-Drive: Enhancing Diffusion Generative Driving Policies with Reward Modeling and Reinforcement Learning Fine-Tuning. ICRA Zhiyu Huang, Xinshuo Weng, Maximilian Igl, Yuxiao Chen, Yulong Cao, Boris Ivanovic, Marco Pavone, Chen Lv
2025	J	`jnl`	LEAD: Minimizing Learner-Expert Asymmetry in End-to-End Driving. CoRR Long Nguyen, Micha Fauth, Bernhard Jaeger, Daniel Dauner, Maximilian Igl, Andreas Geiger, Kashyap Chitta
2025	J	`jnl`	RoaD: Rollouts as Demonstrations for Closed-Loop Supervised Fine-Tuning of Autonomous Driving Policies. CoRR Guillermo Garcia-Cobo, Maximilian Igl, Péter Karkus, Zhejun Zhang, Michael Watson, Yuxiao Chen, Boris Ivanovic, Marco Pavone
2025	A*	`conf`	STORM: Spatio-TempOral Reconstruction Model For Large-Scale Outdoor Scenes. ICLR Jiawei Yang, Jiahui Huang, Boris Ivanovic, Yuxiao Chen, Yan Wang, Boyi Li, Yurong You, Apoorva Sharma, Maximilian Igl, Péter Karkus, Danfei Xu, Yue Wang, Marco Pavone
2025	J	`jnl`	STORM: Spatio-Temporal Reconstruction Model for Large-Scale Outdoor Scenes. CoRR Jiawei Yang, Jiahui Huang, Yuxiao Chen, Yan Wang, Boyi Li, Yurong You, Apoorva Sharma, Maximilian Igl, Péter Karkus, Danfei Xu, Boris Ivanovic, Yue Wang, Marco Pavone
2024	J	`jnl`	Closed-Loop Supervised Fine-Tuning of Tokenized Traffic Models. CoRR Zhejun Zhang, Péter Karkus, Maximilian Igl, Wenhao Ding, Yuxiao Chen, Boris Ivanovic, Marco Pavone
2024	J	`jnl`	Gen-Drive: Enhancing Diffusion Generative Driving Policies with Reward Modeling and Reinforcement Learning Fine-tuning. CoRR Zhiyu Huang, Xinshuo Weng, Maximilian Igl, Yuxiao Chen, Yulong Cao, Boris Ivanovic, Marco Pavone, Chen Lv
2023	A	`conf`	Hierarchical Imitation Learning for Stochastic Environments. IROS Maximilian Igl, Punit Shah, Paul Mougin, Sirish Srinivasan, Tarun Gupta, Brandyn White, Kyriacos Shiarlis, Shimon Whiteson
2023	J	`jnl`	Hierarchical Imitation Learning for Stochastic Environments. CoRR Maximilian Igl, Punit Shah, Paul Mougin, Sirish Srinivasan, Tarun Gupta, Brandyn White, Kyriacos Shiarlis, Shimon Whiteson
2022	A*	`conf`	Communicating via Markov Decision Processes. ICML Samuel Sokota, Christian A. Schröder de Witt, Maximilian Igl, Luisa M. Zintgraf, Philip H. S. Torr, Martin Strohmeier, J. Zico Kolter, Shimon Whiteson, Jakob N. Foerster
2022	—	`conf`	Learning Skills Diverse in Value-Relevant Features. CoLLAs Matthew J. A. Smith, Jelena Luketina, Kristian Hartikainen, Maximilian Igl, Shimon Whiteson
2022	Misc	`conf`	Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving. CoRL Angad Singh, Omar Makhlouf, Maximilian Igl, João V. Messias, Arnaud Doucet, Shimon Whiteson
2022	J	`jnl`	Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving. CoRR Angad Singh, Omar Makhlouf, Maximilian Igl, João V. Messias, Arnaud Doucet, Shimon Whiteson
2022	A*	`conf`	Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation. ICRA Maximilian Igl, Daewoo Kim, Alex Kuefler, Paul Mougin, Punit Shah, Kyriacos Shiarlis, Dragomir Anguelov, Mark Palatucci, Brandyn White, Shimon Whiteson
2022	J	`jnl`	Symphony: Learning Realistic and Diverse Agents for Autonomous Driving Simulation. CoRR Maximilian Igl, Daewoo Kim, Alex Kuefler, Paul Mougin, Punit Shah, Kyriacos Shiarlis, Dragomir Anguelov, Mark Palatucci, Brandyn White, Shimon Whiteson
2021	A*	`conf`	Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning. ICML Luisa M. Zintgraf, Leo Feng, Cong Lu, Maximilian Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson
2021	J	`jnl`	Implicit Communication as Minimum Entropy Coupling. CoRR Samuel Sokota, Christian Schröder de Witt, Maximilian Igl, Luisa M. Zintgraf, Philip H. S. Torr, Shimon Whiteson, Jakob N. Foerster
2021	—	`—`	Inductive biases and generalisation for deep reinforcement learning Maximilian Igl
2021	A*	`conf`	My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control. ICLR Vitaly Kurin, Maximilian Igl, Tim Rocktäschel, Wendelin Boehmer, Shimon Whiteson
2021	J	`jnl`	Snowflake: Scaling GNNs to High-Dimensional Continuous Control via Parameter Freezing. CoRR Charlie Blake, Vitaly Kurin, Maximilian Igl, Shimon Whiteson
2021	A*	`conf`	Snowflake: Scaling GNNs to high-dimensional continuous control via parameter freezing. NeurIPS Charlie Blake, Vitaly Kurin, Maximilian Igl, Shimon Whiteson
2021	A*	`conf`	Transient Non-stationarity and Generalisation in Deep Reinforcement Learning. ICLR Maximilian Igl, Gregory Farquhar, Jelena Luketina, Wendelin Boehmer, Shimon Whiteson
2021	J	`jnl`	VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning. J. Mach. Learn. Res. Luisa M. Zintgraf, Sebastian Schulze, Cong Lu, Leo Feng, Maximilian Igl, Kyriacos Shiarlis, Yarin Gal, Katja Hofmann, Shimon Whiteson
2020	J	`jnl`	Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning. CoRR Luisa M. Zintgraf, Leo Feng, Maximilian Igl, Kristian Hartikainen, Katja Hofmann, Shimon Whiteson
2020	A	`conf`	Multitask Soft Option Learning. UAI Maximilian Igl, Andrew Gambardella, Jinke He, Nantas Nardelli, N. Siddharth, Wendelin Boehmer, Shimon Whiteson
2020	J	`jnl`	My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control. CoRR Vitaly Kurin, Maximilian Igl, Tim Rocktäschel, Wendelin Boehmer, Shimon Whiteson
2020	J	`jnl`	The Impact of Non-stationarity on Generalisation in Deep Reinforcement Learning. CoRR Maximilian Igl, Gregory Farquhar, Jelena Luketina, Wendelin Boehmer, Shimon Whiteson
2020	A*	`conf`	VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning. ICLR Luisa M. Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson
2019	A*	`conf`	Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck. NeurIPS Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann
2019	J	`jnl`	Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck. CoRR Maximilian Igl, Kamil Ciosek, Yingzhen Li, Sebastian Tschiatschek, Cheng Zhang, Sam Devlin, Katja Hofmann
2019	J	`jnl`	Multitask Soft Option Learning. CoRR Maximilian Igl, Andrew Gambardella, Nantas Nardelli, N. Siddharth, Wendelin Böhmer, Shimon Whiteson
2019	J	`jnl`	VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning. CoRR Luisa M. Zintgraf, Kyriacos Shiarlis, Maximilian Igl, Sebastian Schulze, Yarin Gal, Katja Hofmann, Shimon Whiteson
2018	—	`conf`	Auto-Encoding Sequential Monte Carlo. ICLR (Poster) Tuan Anh Le, Maximilian Igl, Tom Rainforth, Tom Jin, Frank Wood
2018	A*	`conf`	Deep Variational Reinforcement Learning for POMDPs. ICML Maximilian Igl, Luisa M. Zintgraf, Tuan Anh Le, Frank Wood, Shimon Whiteson
2018	J	`jnl`	Deep Variational Reinforcement Learning for POMDPs. CoRR Maximilian Igl, Luisa M. Zintgraf, Tuan Anh Le, Frank Wood, Shimon Whiteson
2018	A*	`conf`	Tighter Variational Bounds are Not Necessarily Better. ICML Tom Rainforth, Adam R. Kosiorek, Tuan Anh Le, Chris J. Maddison, Maximilian Igl, Frank Wood, Yee Whye Teh
2018	J	`jnl`	Tighter Variational Bounds are Not Necessarily Better. CoRR Tom Rainforth, Adam R. Kosiorek, Tuan Anh Le, Chris J. Maddison, Maximilian Igl, Frank Wood, Yee Whye Teh
2018	—	`conf`	TreeQN and ATreeC: Differentiable Tree-Structured Models for Deep Reinforcement Learning. ICLR (Poster) Gregory Farquhar, Tim Rocktäschel, Maximilian Igl, Shimon Whiteson
2017	J	`jnl`	TreeQN and ATreeC: Differentiable Tree Planning for Deep Reinforcement Learning. CoRR Gregory Farquhar, Tim Rocktäschel, Maximilian Igl, Shimon Whiteson