Claas Voelcker

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Amir-massoud FarahmandUniversity of TorontoPatvirtintas el. paštas cs.toronto.edu
Marcel HussingUniversity of PennsylvaniaPatvirtintas el. paštas seas.upenn.edu
Kristian KerstingProfessor of AI & ML, TU Darmstadt, Co-Director hessian.ai, DFKI, Germany, CLAIRE & ELLISPatvirtintas el. paštas cs.tu-darmstadt.de
Karl StelznerTU DarmstadtPatvirtintas el. paštas cs.tu-darmstadt.de
Jannik KossenUniversity of OxfordPatvirtintas el. paštas cs.ox.ac.uk
Animesh GargGeorgia Institute of Technology, University of Toronto, NvidiaPatvirtintas el. paštas gatech.edu
Igor GilitschenskiAssistant Professor, University of TorontoPatvirtintas el. paštas cs.toronto.edu
Victor LiaoMaster's Student at University of WaterlooPatvirtintas el. paštas uwaterloo.ca
Romina AbachiUniversity of Toronto, Vector InstitutePatvirtintas el. paštas mail.utoronto.ca
Arash AhmadianCohere For AIPatvirtintas el. paštas cohere.com
Alejandro MolinaAmazonPatvirtintas el. paštas amazon.com

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Claas Voelcker

PhD student at University of Toronto

Patvirtintas el. paštas cs.toronto.edu

machine learning probabilistic models artificial intelligence reinforcement learning


Pavadinimas Rūšiuoti pagal šaltinius Rūšiuoti pagal metus Rūšiuoti pagal pavadinimą	Cituota Cituota	Metai
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	67	2019
Value Gradient weighted Model-Based Reinforcement Learning C Voelcker, V Liao, A Garg, A Farahmand International Conference on Learning Representations, 2022	26	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	18	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
Dissecting Deep RL with High Update Ratios: Combatting Value Divergence M Hussing, C Voelcker, I Gilitschenski, A Farahmand, E Eaton
Local-Forward: Towards Biological Plausibility in Deep Reinforcement Learning J Guan, SE Verch, CA Voelcker, EC Jackson, N Papernot, ...

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