Quentin Delfosse
Scholar

Quentin Delfosse

Google Scholar ID: k1E0FgIAAAAJ
AIML Lab Technische Universität Darmstadt
RoboticsArtificial IntelligenceOpen Ended LearningIntrinsic Motivation
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Citations & Impact
All-time
Citations
318
 
H-index
11
 
i10-index
11
 
Publications
20
 
Co-authors
0
 
Contact
No contact links provided.
Publications
8 items
Boosting deep Reinforcement Learning using pretraining with Logical Options
2026
Cited
0
STORM: Segment, Track, and Object Re-Localization from a Single 3D Model
2025
Cited
0
Deep Reinforcement Learning Agents are not even close to Human Intelligence
2025
Cited
0
Better Decisions through the Right Causal World Model
2025
Cited
0
Deep Reinforcement Learning via Object-Centric Attention
2025
Cited
0
Evaluating Interpretable Reinforcement Learning by Distilling Policies into Programs
2025
Cited
0
Interpretable end-to-end Neurosymbolic Reinforcement Learning agents
arXiv.org · 2024
Cited
5
BlendRL: A Framework for Merging Symbolic and Neural Policy Learning
arXiv.org · 2024
Cited
3
Resume (English only)
Education
  • PhD, Computer Science, Stanford University, 2015-2020, Advisor: Dr. Jane Doe; MSc, Data Science, MIT, 2013-2015.
Background
  • Research interests: Machine Learning, Artificial Intelligence. Bio: A dedicated researcher in the field of AI...
Co-authors
0 total
Co-authors: 0 (list not available)