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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), pp. 31755 - 31768 (Eds. Koyejo, S.; Mohamed, S.). Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA, USA, November 28, 2022 - December 09, 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), pp. 36706 - 36721 (Eds. Koyejo, S.; Mohamed, S.). Thirty-sixth Conference on Neural Information Processing Systems (NeurIPS 2022), New Orleans, LA, USA, November 28, 2022 - December 09, 2022. Curran, Red Hook, NY, USA (2023)

Giannakakis, E.; Khajehabdollahi, S.; Levina, A.: Environmental variability and network structure determine the optimal plasticity mechanisms in embodied agents. In: ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference, pp. 157 - 166 (Eds. Iizuka, H.; Suzuki, K.; Uno, R.; Damiano, L.; Spychala, N. et al.). ALIFE 2023: Ghost in the Machine: The 2021 Conference on Artificial Life, Sapporo, Japan, July 24, 2023 - July 28, 2023. MIT Press (2023)

Khajehabdollahi, S.; Giannakakis, E.; Buendia, V.; Martius, G.; Levina, A.: Locally adaptive cellular automata for goal-oriented self-organization. In: ALIFE 2023: Ghost in the Machine: Proceedings of the 2023 Artificial Life Conference, pp. 410 - 419 (Eds. Iizuka, H.; Suzuki, K.; Uno, R.; Damiano, L.; Spychala, N. et al.). ALIFE 2023: Ghost in the Machine: The 2021 Conference on Artificial Life, Sapporo, Japan, July 24, 2023 - July 28, 2023. MIT Press (2023)

Mahler, L.; Wang, Q.; Steiglechner, J.; Birk, F.; Heczko, S.; Scheffler, K.; Lohmann, G.: Pretraining is All You Need: A Multi-Atlas Enhanced Transformer Framework for Autism Spectrum Disorder Classification. In: Machine Learning in Clinical Neuroimaging: 6th International Workshop, MLCN 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, pp. 123 - 132 (Eds. Abdulkadir, A.; Bathula, D.; Dvornek, N.; Govindarajan, S.; Habes, M. et al.). 6th International Workshop on Machine Learning in Clinical Neuroimaging (MLCN 2023), Vancouver, BC, Canada, October 08, 2023. Springer, Cham, Switzerland (2023)

Wang, Q.; Mahler, L.; Steiglechner, J.; Birk, F.; Scheffler, K.; Lohmann, G.: A Three-Player GAN for Super-Resolution in Magnetic Resonance Imaging. In: Machine Learning in Clinical Neuroimaging: 6th International Workshop, MLCN 2023, Held in Conjunction with MICCAI 2023, Vancouver, BC, Canada, October 8, 2023, pp. 23 - 33 (Eds. Abdulkadir, A.; Bathula, D.; Dvornek, N.; Govindarajan, S.; Habes, M. et al.). 6th International Workshop on Machine Learning in Clinical Neuroimaging (MLCN 2023), Vancouver, BC, Canada, October 08, 2023. Springer, Cham, Switzerland (2023)

Alon, N.; Schulz, L.; Rosenschein, J.; Dayan, P.: A (dis-)information theory of revealed and unrevealed preferences. In: Information-Theoretic Principles in Cognitive Systems: Workshop at the 36th Conference on Neural Information Processing Systems (NeurIPS 2022). NeurIPS 2022 Workshop on Information-Theoretic Principles in Cognitive Systems, New Orleans, LA, USA, December 03, 2022. (2022)

Glang, F.; Nikulin, A.; Bause, J.; Heule, R.; Steffen, T.; Avdievich, N.; Scheffler, K.: Accelerated MRI at 9.4 T with electronically modulated time-varying receive sensitivities. In: 24. Jahrestagung der Deutschen Sektion der ISMRM (DS-ISMRM 2022), V023, pp. 23 - 29. 24. Jahrestagung der Deutschen Sektion der ISMRM (DS-ISMRM 2022), Aachen, Germany, September 21, 2022 - September 24, 2022. (2022)

Bruijns, S.; The International Brain Laboratory; Dayan, P.: Understanding Learning Trajectories With Infinite Hidden Markov Models. In: 2022 Conference on Cognitive Computational Neuroscience, P-1.19, pp. 64 - 66. Conference on Cognitive Computational Neuroscience (CCN 2022), San Francisco, CA, USA, August 25, 2022 - August 28, 2022. (2022)

Khajehnejad, M.; Habibollahi, F.; Nock, R.; Arabzadeh, E.; Dayan, P.; Dezfouli, A.: Neural Network Poisson Models for Behavioural and Neural Spike Train Data. In: International Conference on Machine Learning, 17-23 July 2022, Baltimore, Maryland, USA, pp. 10974 - 10996 (Eds. Chaudhuri, K.; Jegelka, S.; Song, L.; Szepesvari, C.; Niu, G. et al.). Thirty-ninth International Conference on Machine Learning (ICML 2022), Baltimore, MD, USA, July 17, 2022 - July 23, 2022. (2022)

Renz, F.; Grossman, S.; Dayan, P.; Doeller, C.; Schuck, N.: Representation learning facilitates different levels of generalization. In: 2022 Conference on Cognitive Computational Neuroscience, P-2.66, pp. 460 - 462. Conference on Cognitive Computational Neuroscience (CCN 2022), San Francisco, CA, USA, August 25, 2022 - August 28, 2022. (2022)

Schütt, H.; Kipnis, A.; Diedrichsen, J.; Kriegeskorte, N.: Statistical inference on representational geometries. In: 2022 Conference on Cognitive Computational Neuroscience, P-3.54, pp. 663 - 665. Conference on Cognitive Computational Neuroscience (CCN 2022), San Francisco, CA, USA, August 25, 2022 - August 28, 2022. (2022)

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, pp. 976 - 982 (Eds. Culbertson, J.; Perfors, A.; Rabagliati, H.; Ramenzoni, V.). 44th Annual Meeting of the Cognitive Science Society (CogSci 2022): Cognitive Diversity, Toronto, Canada, July 27, 2022 - July 30, 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, pp. 2940 - 2946 (Eds. Culbertson, J.; Perfors, A.; Rabagliati, H.; Ramenzoni, V.). 44th Annual Meeting of the Cognitive Science Society (CogSci 2022): Cognitive Diversity, Toronto, Canada, July 27, 2022 - July 30, 2022. (2022)

Steiglechner, J.; Wang, Q.; Ramadan, D.; Mahler, L.; Scheffler, K.; Bender, B.; Lindig, T.; Lohmann, G.: FLEXseg: Next Generation Brain MRI Segmentation at 9.4 T. In: Medical Imaging with Deep Learning (MIDL 2022). Medical Imaging with Deep Learning (MIDL 2022), Zürich, Swtzerland, July 06, 2022 - July 08, 2022. (2022)

Wang, Q.; Steiglechner, J.; Lindig, T.; Bender, B.; Scheffler, K.; Lohmann, G.: Super-Resolution for Ultra High-Field MR Images. In: Medical Imaging with Deep Learning (MIDL 2022). Medical Imaging with Deep Learning (MIDL 2022) , Zürich, Swtzerland , July 06, 2022 - July 08, 2022. (2022)

Bröker, F.; Roads, B.; Dayan, P.; Love, B.: Teaching categories to human semi-supervised learners. In: 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2022), 2.8, pp. 122 - 125. 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2022), Providence, RI, USA, June 08, 2022 - June 11, 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, pp. 275 - 279. 5th Multidisciplinary Conference on Reinforcement Learning and Decision Making (RLDM 2022), Providence, RI, USA, June 08, 2022 - June 11, 2022. (2022)

Özkurt, S.; Fichter, W.; Fischer, C.; Bülthoff, H.: On the Impact of Flight Control Systems on Kinetosis of Helicopter Passengers. In: 78th Annual Vertical Flight Society Forum and Technology Display (FORUM 78): The Future of Vertical Flight, 44, pp. 304 - 315. 78th Annual Forum & Technology Display of the Vertical Flight Society (VFS 2022), Fort Worth, TX, USA, May 10, 2022 - May 12, 2022. Curran, Red Hook, NY, USA (2022)

Bashiri, M.; Walker, E.; Lurz, K.-K.; Jagadish, A.; Muhammad, T.; Ding, Z.; Ding, Z.; Tolias, A.; Sinz, F.: A flow-based latent state generative model of neural population responses to natural images. In: Advances in Neural Information Processing Systems 34: 35th Conference on Neural Information Processing Systems (NeurIPS 2021), pp. 15801 - 15815 (Eds. Ranzato, M.; Beygelzimer, A.; Liang, P.; Vaughan, J.; Dauphin, Y.). Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021), December 06, 2021 - December 14, 2021. Curran, Red Hook, NY, USA (2022)