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MATTHIEU GEIST
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Name
Affiliation
Papers
MATTHIEU GEIST
Supélec, IMS Research Group, Metz, France and MCE Department, ArcelorMittal Research, Maizières-lès-Metz, France
98
Collaborators
Citations
PageRank
172
385
44.31
Referers
Referees
References
686
768
796
Search Limit
100
768
Publications (98 rows)
Collaborators (100 rows)
Referers (100 rows)
Referees (100 rows)
Title
Citations
PageRank
Year
Lazy-MDPs: Towards Interpretable RL by Learning When to Act.
0
0.34
2022
Continuous Control with Action Quantization from Demonstrations.
0
0.34
2022
A general class of surrogate functions for stable and efficient reinforcement learning
0
0.34
2022
Generalization in Mean Field Games by Learning Master Policies.
0
0.34
2022
Implicitly Regularized RL with Implicit Q-values
0
0.34
2022
Scaling Mean Field Games by Online Mirror Descent.
0
0.34
2022
Offline Reinforcement Learning as Anti-exploration.
0
0.34
2022
Concave Utility Reinforcement Learning: The Mean-field Game Viewpoint.
0
0.34
2022
Scalable Deep Reinforcement Learning Algorithms for Mean Field Games.
0
0.34
2022
Offline Reinforcement Learning With Pseudometric Learning
0
0.34
2021
Show me the Way: Intrinsic Motivation from Demonstrations
0
0.34
2021
How To Train Your Heron
0
0.34
2021
Mean Field Games Flock! The Reinforcement Learning Way.
0
0.34
2021
Adversarially Guided Actor-Critic
0
0.34
2021
Self-Imitation Advantage Learning
0
0.34
2021
What Matters for On-Policy Deep Actor-Critic Methods? A Large-Scale Study
0
0.34
2021
Hyperparameter Selection for Imitation Learning
0
0.34
2021
What Matters for Adversarial Imitation Learning?
0
0.34
2021
Primal Wasserstein Imitation Learning
0
0.34
2021
Fictitious Play for Mean Field Games: Continuous Time Analysis and Applications
0
0.34
2020
On The Convergence Of Model Free Learning In Mean Field Games
0
0.34
2020
Self-Attentional Credit Assignment for Transfer in Reinforcement Learning
1
0.36
2020
Foolproof Cooperative Learning.
0
0.34
2020
Image-Based Place Recognition on Bucolic Environment Across Seasons From Semantic Edge Description.
0
0.34
2020
CopyCAT:: Taking Control of Neural Policies with Constant Attacks
0
0.34
2020
Leverage the Average: an Analysis of KL Regularization in Reinforcement Learning
0
0.34
2020
Munchausen Reinforcement Learning
0
0.34
2020
Deep Conservative Policy Iteration
0
0.34
2019
Stable and Efficient Policy Evaluation.
1
0.41
2019
Targeted Attacks on Deep Reinforcement Learning Agents through Adversarial Observations.
0
0.34
2019
A Theory of Regularized Markov Decision Processes.
0
0.34
2019
Learning from a Learner
0
0.34
2019
Image-Based Text Classification using 2D Convolutional Neural Networks
0
0.34
2019
Foolproof Cooperative Learning.
0
0.34
2019
Importance Sampling for Deep System Identification
0
0.34
2019
A Deep Learning Approach For Privacy Preservation In Assisted Living
1
0.35
2018
Human Activity Recognition Using Recurrent Neural Networks.
10
0.62
2018
Image-based Natural Language Understanding Using 2D Convolutional Neural Networks.
0
0.34
2018
Anderson Acceleration for Reinforcement Learning.
0
0.34
2018
Deep Representation Learning for Domain Adaptation of Semantic Image Segmentation.
0
0.34
2018
Reconstruct & Crush Network.
0
0.34
2017
Is the Bellman residual a bad proxy?
0
0.34
2017
Bridging the Gap Between Imitation Learning and Inverse Reinforcement Learning.
7
0.51
2017
Should one minimize the expected Bellman residual or maximize the mean value?
0
0.34
2016
Difference of Convex Functions Programming Applied to Control with Expert Data.
0
0.34
2016
Score-based Inverse Reinforcement Learning.
0
0.34
2016
Softened Approximate Policy Iteration for Markov Games.
4
0.42
2016
Imitation Learning Applied to Embodied Conversational Agents
2
0.38
2015
Soft-max boosting
0
0.34
2015
Inverse reinforcement learning in relational domains
4
0.41
2015
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