Claas Völcker

According to our database, Claas Völcker authored at least 11 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

MAD-TD: Model-Augmented Data stabilizes High Update Ratio RL.

Claas Völcker, Marcel Hussing, Eric Eaton, Amir-massoud Farahmand, Igor Gilitschenski

CoRR, 2024

Can we hop in general? A discussion of benchmark selection and design using the Hopper environment.

Claas Völcker, Marcel Hussing, Eric Eaton

CoRR, 2024

Dissecting Deep RL with High Update Ratios: Combatting Value Overestimation and Divergence.

Marcel Hussing, Claas Voelcker, Igor Gilitschenski, Amir-massoud Farahmand, Eric Eaton

CoRR, 2024

When does Self-Prediction help? Understanding Auxiliary Tasks in Reinforcement Learning.

Claas Voelcker, Tyler Kastner, Igor Gilitschenski, Amir-massoud Farahmand

RLJ, 2024

Dissecting Deep RL with High Update Ratios: Combatting Value Divergence.

Marcel Hussing, Claas Voelcker, Igor Gilitschenski, Amir-massoud Farahmand, Eric Eaton

RLJ, 2024

2023

λ-AC: Learning latent decision-aware models for reinforcement learning in continuous state-spaces.

Claas Voelcker, Arash Ahmadian, Romina Abachi, Igor Gilitschenski, Amir-massoud Farahmand

CoRR, 2023

Queer In AI: A Case Study in Community-Led Participatory AI.

Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J. Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi Jethwani, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx McLean, Pan Xu, Pranav A, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J. Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y. Bilenko, Andrew McNamara, Raphael Gontijo Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, Luke Stark

CoRR, 2023

Queer In AI: A Case Study in Community-Led Participatory AI.

Organizers Of QueerInAI, Anaelia Ovalle, Arjun Subramonian, Ashwin Singh, Claas Voelcker, Danica J. Sutherland, Davide Locatelli, Eva Breznik, Filip Klubicka, Hang Yuan, Hetvi Jethwani, Huan Zhang, Jaidev Shriram, Kruno Lehman, Luca Soldaini, Maarten Sap, Marc Peter Deisenroth, Maria Leonor Pacheco, Maria Ryskina, Martin Mundt, Milind Agarwal, Nyx McLean, Pan Xu, Pranav A, Raj Korpan, Ruchira Ray, Sarah Mathew, Sarthak Arora, St John, Tanvi Anand, Vishakha Agrawal, William Agnew, Yanan Long, Zijie J. Wang, Zeerak Talat, Avijit Ghosh, Nathaniel Dennler, Michael Noseworthy, Sharvani Jha, Emi Baylor, Aditya Joshi, Natalia Y. Bilenko, Andrew McNamara, Raphael Gontijo Lopes, Alex Markham, Evyn Dong, Jackie Kay, Manu Saraswat, Nikhil Vytla, Luke Stark

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

2022

Value Gradient weighted Model-Based Reinforcement Learning.

Claas Voelcker, Victor Liao, Animesh Garg, Amir-massoud Farahmand

Proceedings of the Tenth International Conference on Learning Representations, 2022

2020

Structured Object-Aware Physics Prediction for Video Modeling and Planning.

Jannik Kossen, Karl Stelzner, Marcel Hussing, Claas Voelcker, Kristian Kersting

Proceedings of the 8th International Conference on Learning Representations, 2020

2019

DeepNotebooks: Deep Probabilistic Models Construct Python Notebooks for Reporting Datasets.

Claas Völcker, Alejandro Molina, Johannes Neumann, Dirk Westermann, Kristian Kersting

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019