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Claas Völcker
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2020 – today
- 2024
- [j2]Marcel Hussing, Claas Voelcker, Igor Gilitschenski, Amir-massoud Farahmand, Eric Eaton:
Dissecting Deep RL with High Update Ratios: Combatting Value Divergence. RLJ 2: 995-1018 (2024) - [j1]Claas Voelcker, Tyler Kastner, Igor Gilitschenski, Amir-massoud Farahmand:
When does Self-Prediction help? Understanding Auxiliary Tasks in Reinforcement Learning. RLJ 4: 1567-1597 (2024) - [i8]Marcel Hussing, Claas Voelcker, Igor Gilitschenski, Amir-massoud Farahmand, Eric Eaton:
Dissecting Deep RL with High Update Ratios: Combatting Value Overestimation and Divergence. CoRR abs/2403.05996 (2024) - [i7]Claas Voelcker, Tyler Kastner, Igor Gilitschenski, Amir-massoud Farahmand:
When does Self-Prediction help? Understanding Auxiliary Tasks in Reinforcement Learning. CoRR abs/2406.17718 (2024) - [i6]Claas Völcker, Marcel Hussing, Eric Eaton:
Can we hop in general? A discussion of benchmark selection and design using the Hopper environment. CoRR abs/2410.08870 (2024) - [i5]Claas Völcker, Marcel Hussing, Eric Eaton, Amir-massoud Farahmand, Igor Gilitschenski:
MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL. CoRR abs/2410.08896 (2024) - 2023
- [c4]Organizers Of QueerInAI
, Anaelia Ovalle
Queer In AI: A Case Study in Community-Led Participatory AI. FAccT 2023: 1882-1895 - [i4]Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J. Sutherland, Davide Locatelli
Queer In AI: A Case Study in Community-Led Participatory AI. CoRR abs/2303.16972 (2023) - [i3]Claas Voelcker, Arash Ahmadian, Romina Abachi, Igor Gilitschenski, Amir-massoud Farahmand:
λ-AC: Learning latent decision-aware models for reinforcement learning in continuous state-spaces. CoRR abs/2306.17366 (2023) - 2022
- [c3]Claas Voelcker, Victor Liao, Animesh Garg, Amir-massoud Farahmand:
Value Gradient weighted Model-Based Reinforcement Learning. ICLR 2022 - [i2]Claas Voelcker, Victor Liao, Animesh Garg, Amir-massoud Farahmand:
Value Gradient weighted Model-Based Reinforcement Learning. CoRR abs/2204.01464 (2022) - 2020
- [c2]Jannik Kossen, Karl Stelzner, Marcel Hussing, Claas Voelcker, Kristian Kersting:
Structured Object-Aware Physics Prediction for Video Modeling and Planning. ICLR 2020
2010 – 2019
- 2019
- [c1]Claas Völcker, Alejandro Molina, Johannes Neumann
DeepNotebooks: Deep Probabilistic Models Construct Python Notebooks for Reporting Datasets. PKDD/ECML Workshops (1) 2019: 28-43 - [i1]Jannik Kossen, Karl Stelzner, Marcel Hussing, Claas Voelcker, Kristian Kersting:
Structured Object-Aware Physics Prediction for Video Modeling and Planning. CoRR abs/1910.02425 (2019)
Coauthor Index
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