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Jürgen Schmidhuber

Hierarchical Reinforcement Learning Based on Subgoal Discovery and Subpolicy Specialization
2004 · Bram Bakker, Jürgen Schmidhuber · 114
Self-Improvements in Modern Agentic Systems: A Survey
2026 · Ren, Zhe, Chen, Yimeng, et al. · arXiv (Cornell University) · 32
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The Modular Behavioral Environment for Humanoids and other Robots (MoBeE)
2012 · Mikhail Frank, Jürgen Leitner, et al. · International Conference on Informatics in Control, Automation and Robotics (ICINCO) · 18
How Much Can We Trust LLM Search Agents? Measuring Endorsement Vulnerability to Web Content Manipulation
2026 · Yimeng Chen, Zhe Ren, et al. · Conference on Empirical Methods in Natural Language Processing (EMNLP) · 9
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Neural Computers
2026 · Zhuge, Mingchen, Zhao, Changsheng, et al. · arXiv (Cornell University) · 7
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Fast and scalable retrosynthetic planning with a transformer neural network and speculative beam search
2026 · Natalia Andronova, Mikhail Andronov, et al. · Digital Discovery · 6
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Contrastive Training of Complex-Valued Autoencoders for Object Discovery
2023 · Aleksandar Stanic, Anand Gopalakrishnan, et al. · neural information processing systems · 6
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Artificial Neural Networks and Machine Learning – ICANN 2024
2024 · Michael Wand, Kristína Malinovská, et al. · Lecture notes in computer science · 5
DiG-bench: Discovery in Games
2026 · Battleday, Ruairidh M., Sandbrink, Kai, et al. · arXiv (Cornell University) · 4
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AI in Drug Discovery
2024 · Djork-Arné Clevert, Michael Wand, et al. · Lecture notes in computer science · 4
Artificial Neural Networks and Machine Learning – ICANN 2024
2024 · Michael Wand, Kristína Malinovská, et al. · Lecture notes in computer science · 4
Interestingness as an Inductive Heuristic for Future Compression Progress
2026 · Herrmann, Vincent, Schmidhuber, Jürgen · arXiv (Cornell University) · 3
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Hybrid Advantage Estimation with Unified Critic for VLM Agentic Reinforcement Learning
2026 · Wenxuan Zhang, Yuhui Wang, et al. · Lecture notes in computer science · 3
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Exploring Through Random Curiosity with General Value Functions
2022 · Aditya Ramesh, Louis Kirsch, et al. · neural information processing systems · 3
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SciDiagramEdit: Learning to Edit Scientific Diagrams from Paper Revisions
2026 · Sun, Yasheng, Zeng, Zezi, et al. · arXiv (Cornell University) · 2
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Planning to Explore: Curiosity-Driven Planning for LLM Test Generation
2026 · Amayuelas, Alfonso, Laakom, Firas, et al. · arXiv (Cornell University) · 2
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RACAS: Controlling Diverse Robots With a Single Agentic System
2026 · Ashley, Dylan R., Przepióra, Jan, et al. · arXiv (Cornell University) · 2
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Artificial Neural Networks and Machine Learning – ICANN 2024
2024 · Michael Wand, Kristína Malinovská, et al. · Lecture notes in computer science · 2
Artificial Neural Networks and Machine Learning – ICANN 2024
2024 · Michael Wand, Kristína Malinovská, et al. · Lecture notes in computer science · 2
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Predictive Semantic Safety: From Visual Physical Reasoning to Safety-Critical Control
2026 · Kim, Taekyung, Fradi, Salem, et al. · arXiv (Cornell University) · 1
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Learning to Forget: Continual Learning with Adaptive Weight Decay
2026 · Ramesh, Aditya A., Lewandowski, Alex, et al. · arXiv (Cornell University) · 1
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Artificial Neural Networks and Machine Learning – ICANN 2024
2024 · Michael Wand, Kristína Malinovská, et al. · Lecture notes in computer science · 1
Artificial Neural Networks and Machine Learning – ICANN 2024
2024 · Michael Wand, Kristína Malinovská, et al. · Lecture notes in computer science · 1
Artificial Neural Networks and Machine Learning – ICANN 2024
2024 · Michael Wand, Kristína Malinovská, et al. · Lecture notes in computer science · 1
Artificial Neural Networks and Machine Learning – ICANN 2024
2024 · Michael Wand, Kristína Malinovská, et al. · Lecture notes in computer science · 1
Works count: 49
Citation count: 319
H-index: 7
I10-index: 5
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