Maximilian Igl
17 papers · 2018–2026 · 7 venues · across top CS/AI venues
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variational inference
(4)
task uncertainty
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multi-task learning
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generative model
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reinforcement learning
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evidence lower bound
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sim-to-real transfer
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bayesian inference
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transfer learning
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particle filtering
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information bottleneck
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knowledge transfer
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behavior cloning
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approximate inference
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hierarchical reinforcement learning
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neural rendering
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domain generalization
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scene reconstruction
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Papers
LEAD: Minimizing Learner-Expert Asymmetry in End-to-End Driving
CVPR 2026
Closed-Loop Supervised Fine-Tuning of Tokenized Traffic Models
CVPR 2025
STORM: Spatio-TempOral Reconstruction Model For Large-Scale Outdoor Scenes
ICLR 2025
Communicating via Markov Decision Processes
ICML 2022
Particle-Based Score Estimation for State Space Model Learning in Autonomous Driving
CoRL 2022
Exploration in Approximate Hyper-State Space for Meta Reinforcement Learning
ICML 2021
My Body is a Cage: the Role of Morphology in Graph-Based Incompatible Control
ICLR 2021
Snowflake: Scaling GNNs to high-dimensional continuous control via parameter freezing
NeurIPS 2021
Transient Non-stationarity and Generalisation in Deep Reinforcement Learning
ICLR 2021
VariBAD: Variational Bayes-Adaptive Deep RL via Meta-Learning
JMLR 2021
Multitask Soft Option Learning
UAI 2020
VariBAD: A Very Good Method for Bayes-Adaptive Deep RL via Meta-Learning
ICLR 2020
Generalization in Reinforcement Learning with Selective Noise Injection and Information Bottleneck
NeurIPS 2019
Auto-Encoding Sequential Monte Carlo
ICLR 2018
Deep Variational Reinforcement Learning for POMDPs
ICML 2018
Tighter Variational Bounds are Not Necessarily Better
ICML 2018
TreeQN and ATreeC: Differentiable Tree-Structured Models for Deep Reinforcement Learning
ICLR 2018