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Nath, S.; Shen, K.; Brielmann, A.; Dayan, P.: Simplicity in Complexity. In: ICLR 2024 Workshop on Representational Alignment (Re-Align). ICLR 2024 Workshop on Representational Alignment (Re-Align), Wien, Austria, May 11, 2024. (2024)

Saanum, T.; Éltetö, N.; Dayan, P.; Binz, M.; Schulz, E.: Reinforcement Learning with Simple Sequence Priors. In: Advances in Neural Information Processing Systems 36: 37th Conference on Neural Information Processing Systems (NeurIPS 2023), 2710, pp. 61985 - 62005 (Eds. Oh, A.; Naumann, T.; Globerson, A.; Saenko, K.; Hardt, M. et al.). Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, LA, USA, December 10, 2023 - December 16, 2023. Curran, Red Hook, NY, USA (2024)

Salewski, L.; Alaniz, S.; Rio-Torto, I.; Schulz, E.; Akata, Z.: In-Context Impersonation Reveals Large Language Models’ Strengths and Biases. In: Advances in Neural Information Processing Systems 36: 37th Conference on Neural Information Processing Systems (NeurIPS 2023), 3152, pp. 72044 - 72057 (Eds. Oh, A.; Naumann, T.; Globerson, A.; Saenko, K.; Hardt, M. et al.). Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, LA, USA, December 10, 2023 - December 16, 2023. Curran, Red Hook, NY, USA (2024)

Spieler, A.; Rahaman, N.; Martius, G.; Schölkopf, B.; Levina, A.: The Expressive Leaky Memory Neuron: an Efficient and Expressive Phenomenological Neuron Model Can Solve Long-Horizon Tasks. In: Twelfth International Conference on Learning Representations 2024: ICLR 2024 (Eds. Kim, B.; Yue, Y.; Chaudhuri, S.; Fragkiadaki, K.; Khan, M. et al.). Twelfth International Conference on Learning Representations (ICLR 2024), Wien, Austria, May 07, 2024 - May 11, 2024. (2024)

Zaiss, M.; Rajput , J.; Dang, H.; Golkov, V.; Cremers, D.; Knoll, F.; Maier, A.: GPT4MR: Exploring GPT-4 as an MR sequence and reconstruction programming assistant. In: Bildverarbeitung für die Medizin 2024: Proceedings, German Conference on Medical Image Computing, Erlangen, March 10-12, 2024, pp. 94 - 99 (Eds. Maier, A.; Deserno, T.; Handels, H.; Maier-Hein, K.; Palm, C. et al.). Bildverarbeitung für die Medizin 2024 (BVM 2024), Erlangen, Germany, March 10, 2024 - March 12, 2024. Springer Vieweg, Wiesbaden, Germany (2024)

Antonov, G.; Dayan, P.: Exploring Uncertainty in Distributional Reinforcement Learning. Reinforcement Learning Conference (RLC 2024), Amherst, MA, USA, August 09, 2024 - August 12, 2024. Reinforcement Learning Journal 2, pp. 961 - 978 (2024)

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, Vol. 235, pp. 9076 - 9108. 41st International Conference on Machine Learning (ICML 2024), Wien, Austria, July 21, 2024 - July 27, 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, Vol. 235, pp. 21121 - 21147. 41st International Conference on Machine Learning (ICML 2024), Wien, Austria, July 21, 2024 - July 27, 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, Vol. 235, pp. 43928 - 43946. 41st International Conference on Machine Learning (ICML 2024), Wien, Austria, July 21, 2024 - July 27, 2024. (2024)

Bucher, S.; Dayan, P.: Cognitive Information Filters: Algorithmic Choice Architecture for Boundedly Rational Consumers. In: NeurIPS 2023 workshop: Information-Theoretic Principles in Cognitive Systems: InfoCog@NeurIPS2023. NeurIPS 2023 workshop: Information-Theoretic Principles in Cognitive Systems: InfoCog@NeurIPS2023, New Orleans, LA, USA, December 15, 2023. (2023)

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, December 16, 2023. (2023)

Teng, T.; Wenliang, L.; Zhang, H.: Bounded rationality in structured density estimation. In: Thirty-seventh Conference on Neural Information Processing Systems (NeurIPS 2023). Advances in Neural Information Processing Systems 36: 37th Conference on Neural Information Processing Systems (NeurIPS 2023), New Orleans, LA, USA, December 10, 2023 - December 16, 2023. (2023)

Wang, Q.; Mahler, L.; Steiglechner, J.; Birk, F.; Scheffler, K.; Lohmann, G.: DISGAN: Wavelet-informed Discriminator Guides GAN to MRI Super-resolution with Noise Cleaning. In: IEEE/CVF International Conference on Computer Vision (ICCV) Workshops, pp. 2452 - 2461. 2nd Workshop on Computer Vision for Automated Medical Diagnosis: International Conference on Computer Vision (ICCV/CVF 2023) , Paris, France, October 02, 2023 - October 06, 2023. (2023)

Dang, H.; Endres, J.; Weinmüller, S.; Glang, F.; Loktyushin, A.; Scheffler, K.; Doerfler, A.; Schmidt, M.; Maier, A.; Zaiss, M.: MR-zero meets RARE MRI: Joint optimization of refocusing flip angles and neural networks to minimize T2-induced blurring in spin echo sequences. In: DS-ISMRM 2023. 25. Jahrestagung der Deutschen Sektion der ISMRM (DS-ISMRM 2023), Berlin, Germany, September 06, 2023 - September 07, 2023. (2023)

Safavi, S.: Methods for cross-scale analysis of neural data. In: Satellite Workshops of the Bernstein Conference 2023: Multi-modal understanding of brain and behavior. Satellite Workshops of the Bernstein Conference 2023: Multi-modal understanding of brain and behavior, Berlin, Germany, September 26, 2023 - September 27, 2023. (2023)

Zeraati, R.: Flexible control of neural and behavioral dynamics during selective attention. In: Satellite Workshops of the Bernstein Conference 2023: Behavioral flexibility and its neural correlates. Satellite Workshops of the Bernstein Conference 2023: Behavioral flexibility and its neural correlates, Berlin, Germany, September 26, 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, pp. 832 - 835. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, August 24, 2023 - August 27, 2023. (2023)

Bruijns, S.; Dayan, P.; The International Brain Laborartory: Understanding Learning Trajectories With Infinite Hidden Markov Models. In: 2023 Conference on Cognitive Computational Neuroscience, P-2.97, pp. 770 - 772. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, August 24, 2023 - August 27, 2023. (2023)

Ershadmanesh, S.; Gholamzadeh, A.; Desender, K.; Dayan, P.: Meta-cognitive Efficiency in Learned Value-based Choice. In: 2023 Conference on Cognitive Computational Neuroscience, P-1A.9, pp. 29 - 32. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, August 24, 2023 - August 27, 2023. (2023)

Hamidi, M.; Bányai, M.; Wu, C.: One bottleneck is not enough. In: 2023 Conference on Cognitive Computational Neuroscience, P-2B.44, pp. 795 - 798. Conference on Cognitive Computational Neuroscience (CCN 2023), Oxford, UK, August 24, 2023 - August 27, 2023. (2023)