Claas Voelcker 个人学术档案

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Amir-massoud FarahmandUniversity of Toronto在 cs.toronto.edu 的电子邮件经过验证
Marcel HussingUniversity of Pennsylvania在 seas.upenn.edu 的电子邮件经过验证
Kristian KerstingProfessor of AI & ML, TU Darmstadt, Co-Director hessian.ai, DFKI, Germany, CLAIRE & ELLIS在 cs.tu-darmstadt.de 的电子邮件经过验证
Animesh GargGeorgia Institute of Technology, University of Toronto, Nvidia在 gatech.edu 的电子邮件经过验证
Karl StelznerTU Darmstadt在 cs.tu-darmstadt.de 的电子邮件经过验证
Jannik KossenUniversity of Oxford在 cs.ox.ac.uk 的电子邮件经过验证
Igor GilitschenskiAssistant Professor, University of Toronto在 cs.toronto.edu 的电子邮件经过验证
Victor LiaoMaster's Student at University of Waterloo在 uwaterloo.ca 的电子邮件经过验证
Romina AbachiUniversity of Toronto, Vector Institute在 mail.utoronto.ca 的电子邮件经过验证
Eric EatonUniversity of Pennsylvania在 cis.upenn.edu 的电子邮件经过验证
Arash AhmadianCohere For AI在 cohere.com 的电子邮件经过验证
Alejandro MolinaAmazon在 amazon.com 的电子邮件经过验证
William A CunninghamDepartment of Psychology University of Toronto在 utoronto.ca 的电子邮件经过验证
Tyler KastnerUniversity of Toronto在 mail.mcgill.ca 的电子邮件经过验证
Nicolas PapernotUniversity of Toronto and Vector Institute在 utoronto.ca 的电子邮件经过验证
Jonas GuanUniversity of Toronto, Vector Institute在 cs.toronto.edu 的电子邮件经过验证

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Claas Voelcker

PhD student at University of Toronto

在 cs.toronto.edu 的电子邮件经过验证

machine learning probabilistic models artificial intelligence reinforcement learning


标题按引用次数排序按年份排序按标题排序	引用次数引用次数	年份
Structured object-aware physics prediction for video modeling and planning J Kossen, K Stelzner, M Hussing, C Voelcker, K Kersting arXiv preprint arXiv:1910.02425, 2019	68	2019
Value Gradient weighted Model-Based Reinforcement Learning C Voelcker, V Liao, A Garg, A Farahmand International Conference on Learning Representations, 2022	30	2022
Queer in AI: A case study in community-led participatory AI OO Queerinai, A Ovalle, A Subramonian, A Singh, C Voelcker, ... Proceedings of the 2023 ACM Conference on Fairness, Accountability, and …, 2023	23	2023
Dissecting Deep RL with High Update Ratios: Combatting Value Overestimation and Divergence M Hussing, C Voelcker, I Gilitschenski, A Farahmand, E Eaton arXiv preprint arXiv:2403.05996, 2024	4	2024
VIPer: Iterative Value-Aware Model Learning on the Value Improvement Path R Abachi, CA Voelcker, A Garg, A Farahmand Decision Awareness in Reinforcement Learning Workshop at ICML 2022, 2022	3	2022
DeepNotebooks: Deep Probabilistic Models Construct Python Notebooks for Reporting Datasets C Voelcker, A Molina, J Neumann, D Westermann, K Kersting ECMLPKDD Workshop on Automating Data Science, 2019	3	2019
-AC: Learning latent decision-aware models for reinforcement learning in continuous state-spaces CA Voelcker, A Ahmadian, R Abachi, I Gilitschenski, A Farahmand arXiv preprint arXiv:2306.17366, 2023	1	2023
When does Self-Prediction help? Understanding Auxiliary Tasks in Reinforcement Learning C Voelcker, T Kastner, I Gilitschenski, A Farahmand arXiv preprint arXiv:2406.17718, 2024		2024
Queer In AI: A Case Study in Community-Led Participatory AI OOFQIN AI, A OVALLE, A SUBRAMONIAN, A SINGH, C VOELCKER, ... arXiv preprint arXiv:2303.16972, 2023		2023
Can we hop in general? A discussion of benchmark selection and design using the Hopper environment CA Voelcker, M Hussing, E Eaton Finding the Frame: An RLC Workshop for Examining Conceptual Frameworks, 0
Local-Forward: Towards Biological Plausibility in Deep Reinforcement Learning J Guan, SE Verch, CA Voelcker, EC Jackson, N Papernot, ...

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