Publikationen von E Schulz

Coda-Forno, J.; Binz, M.; Wang, J.; Schulz, E.: CogBench: a large language model walks into a psychology lab. In: Proceedings of Machine Learning Research: PLMR, Bd. 235, S. 9076 - 9108. 41st International Conference on Machine Learning (ICML 2024), Wien, Austria, 21. Juli 2024 - 27. Juli 2024. (2024)

Jagadish, A.; Coda-Forno, J.; Thalmann, M.; Schulz, E.; Binz, M.: Human-like Category Learning by Injecting Ecological Priors from Large Language Models into Neural Networks. In: Proceedings of Machine Learning Research: PLMR, Bd. 235, S. 21121 - 21147. 41st International Conference on Machine Learning (ICML 2024), Wien, Austria, 21. Juli 2024 - 27. Juli 2024. (2024)

Schubert, J.; Jagadish, A.; Binz, M.; Schulz, E.: In-Context Learning Agents Are Asymmetric Belief Updaters. In: Proceedings of Machine Learning Research: PLMR, Bd. 235, S. 43928 - 43946. 41st International Conference on Machine Learning (ICML 2024), Wien, Austria, 21. Juli 2024 - 27. Juli 2024. (2024)

Schreiber, A.; Wu, S.; Wu, C.; Indiveri, G.; Schulz, E.: Biologically-plausible hierarchical chunking on mixed-signal neuromorphic hardware. In: NeurIPS 2023 Workshop: Machine Learning with New Compute Paradigms. NeurIPS 2023 Workshop: Machine Learning with New Compute Paradigms, New Orleans, LA, USA, 16. Dezember 2023. (2023)

Brändle, F.; Schulz, E.; Wu, C.: Learning progress and uncompensated rewards as motivational drivers of engagement. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.114, S. 832 - 835. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Haridi, S.; Thalmann, M.; Schulz, E.: Simulating the Scaling of Long-Term Memory Retrieval. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.101, S. 784 - 787. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Hedrich, N.; Hall-McMaster, S.; Schulz, E.; Schuck, N.: Faster learning from slow features: The temporal coherence prior in human reinforcement learning. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.10, S. 458 - 461. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Ludwig, T.; Siegel, M.; Schulz, E.: Human Multi-Task Learning: the Why and What. In: 2023 Conference on Cognitive Computational Neuroscience, P-1.119, S. 418 - 421. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Schubert, J.; Jagadish, A.; Binz, M.; Schulz, E.: A Rational Analysis of the Optimism Bias using Meta-Reinforcement Learning. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.37, S. 557 - 559. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Schulze Buschoff, L.; Schulz, E.; Binz, M.: The Acquisition of Physical Knowledge in Generative Neural Networks. In: 40th International Conference on Machine Learning, S. 30321 - 30341 (Hg. Krause, A.; Brunskill, E.; Cho, K.; Engelhardt, B.; Sabato, S. et al.). Fortieth International Conference on Machine Learning (ICML 2023), Honolulu, HI,USA, 23. Juli 2023 - 29. Juli 2023. (2023)

Thalmann, M.; Schulz, E.: Simple, Idiosyncratic Decision Heuristics in a Two-Armed Bandit Task. In: 2023 Conference on Cognitive Computational Neuroscience, P-3.80, S. 1156 - 1159. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Witte, K.; Schulz, E.; Wise, T.; Huys, Q.: People who worry more explore more. In: 2023 Conference on Cognitive Computational Neuroscience, P-1.101, S. 355 - 357. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Wu, S.; Thalmann, M.; Schulz, E.: Projectional motifs facilitate sequence memorization and transfer. In: 2023 Conference on Cognitive Computational Neuroscience, P-3.118, S. 1294 - 1296. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, 24. August 2023 - 27. August 2023. (2023)

Binz, M.; Schulz, E.: Modeling Human Exploration Through Resource-Rational Reinforcement Learning. In: Advances in Neural Information Processing Systems 35: 36th Conference on Neural Information Processing Systems (NeurIPS 2022), S. 31755 - 31768 (Hg. Koyejo, S.; Mohamed, S.). Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA, USA, 28. November 2022 - 09. Dezember 2022. Curran, Red Hook, NY, USA (2023)

Wu, S.; Éltetö, N.; Dasgupta, I.; Schulz, E.: Learning Structure from the Ground up: Hierarchical Representation Learning by Chunking. In: Advances in Neural Information Processing Systems 35: 36th Conference on Neural Information Processing Systems (NeurIPS 2022), S. 36706 - 36721 (Hg. Koyejo, S.; Mohamed, S.). Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA, USA, 28. November 2022 - 09. Dezember 2022. Curran, Red Hook, NY, USA (2023)

Demircan, C.; Pettini, L.; Saanum, T.; Binz, M.; Baczkowski, B.; Doeller, C.; Garvert, M.; Schulz, E.: Decision-Making with Naturalistic Options. In: 44th Annual Meeting of the Cognitive Science Society (CogSci 2022): Cognitive Diversity, S. 976 - 982 (Hg. Culbertson, J.; Perfors, A.; Rabagliati, H.; Ramenzoni, V.). 44th Annual Meeting of the Cognitive Science Society (CogSci 2022): Cognitive Diversity, Toronto, Canada, 27. Juli 2022 - 30. Juli 2022. (2022)

Ludwig, T.; Wu, C.; Schulz, E.: Connecting Exploration, Generalization, and Planning in Correlated Trees. In: 44th Annual Meeting of the Cognitive Science Society (CogSci 2022): Cognitive Diversity, S. 2940 - 2946 (Hg. Culbertson, J.; Perfors, A.; Rabagliati, H.; Ramenzoni, V.). 44th Annual Meeting of the Cognitive Science Society (CogSci 2022): Cognitive Diversity, Toronto, Canada, 27. Juli 2022 - 30. Juli 2022. (2022)

Jagadish, A.; Saanum, T.; Wang, J.; Binz, M.; Schulz, E.: Probing Compositional Inference in Natural and Artificial Agents. In: 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2022), 1.67, S. 275 - 279. 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2022), Providence, RI, USA, 08. Juni 2022 - 11. Juni 2022. (2022)

Witte, K.; Wise, T.; Schulz, E.: The two faces of anxiety in exploration: Taking risks or playing it safe. In: 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2022), 1.47, S. 32. 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2022), Providence, RI, USA, 08. Juni 2022 - 11. Juni 2022. (2022)

Wu, S.; Éltetö, N.; Dasgupta, I.; Schulz, E.: Learning Structure from the Ground up: Hierarchical Representation Learning by Chunking. In: Tenth International Conference on Learning Representations (ICLR 2022). Tenth International Conference on Learning Representations (ICLR 2022), 25. April 2022 - 29. April 2022. (2022)