Yannick Schroecker

According to our database1, Yannick Schroecker authored at least 15 papers between 2016 and 2023.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

On csauthors.net:

Bibliography

2023
Vision-Language Models as a Source of Rewards.
CoRR, 2023

Human-Timescale Adaptation in an Open-Ended Task Space.
CoRR, 2023

Structured State Space Models for In-Context Reinforcement Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023


Discovering Policies with DOMiNO: Diversity Optimization Maintaining Near Optimality.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

2022
Bootstrapped Meta-Learning.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Meta-Gradients in Non-Stationary Environments.
Proceedings of the Conference on Lifelong Learning Agents, 2022

2020
Manipulating State Space Distributions for Sample-Efficient Imitation-Learning.
PhD thesis, 2020

Universal Value Density Estimation for Imitation Learning and Goal-Conditioned Reinforcement Learning.
CoRR, 2020

2019
Active Learning within Constrained Environments through Imitation of an Expert Questioner.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Imitating Latent Policies from Observation.
Proceedings of the 36th International Conference on Machine Learning, 2019

Generative predecessor models for sample-efficient imitation learning.
Proceedings of the 7th International Conference on Learning Representations, 2019

2017
State Space Decomposition and Subgoal Creation for Transfer in Deep Reinforcement Learning.
CoRR, 2017

State Aware Imitation Learning.
Proceedings of the Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, 2017

2016
Directing Policy Search with Interactively Taught Via-Points.
Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, 2016


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