Publikationen von AK Jagadish

Zeitschriftenartikel (2)

1.
Zeitschriftenartikel
Binz, M.; Dasgupta, I.; Jagadish, A.; Botvinick, M.; Wang, J.; Schulz, E.: Meta-Learned Models of Cognition. Behavioral and Brain Sciences Epub ahead (2023)
2.
Zeitschriftenartikel
Rodriguez, C.; Jagadish, A.; Meskaldji, D.-E.; Haller, S.; Herrmann, F.; Van De Ville, D.; Giannakopoulos, P.: Structural Correlates of Personality Dimensions in Healthy Aging and MCI. Frontiers in Psychology 9, 2652, S. 1 - 13 (2019)

Konferenzbeitrag (4)

3.
Konferenzbeitrag
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)
4.
Konferenzbeitrag
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)
5.
Konferenzbeitrag
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), S. 15801 - 15815 (Hg. Ranzato, M.; Beygelzimer, A.; Liang, P.; Vaughan, J.; Dauphin, Y.). Thirty-fifth Conference on Neural Information Processing Systems (NeurIPS 2021), 06. Dezember 2021 - 14. Dezember 2021. Curran, Red Hook, NY, USA (2022)
6.
Konferenzbeitrag
Lurz, K.-K.; Bashiri, M.; Willeke, K.; Jagadish, A.; Wang, E.; Walker, E.; Cadena, S.; Muhammad, T.; Cobos, E.; Tolias, A. et al.; Ecker, A.; Sinz, F.: Generalization in data-driven models of primary visual cortex. In: Ninth International Conference on Learning Representations (ICLR 2021). Ninth International Conference on Learning Representations (ICLR 2021), Wien, Austria, 03. Mai 2021 - 07. Mai 2021. (2021)

Meeting Abstract (1)

7.
Meeting Abstract
Chen, H.; Jagadish, A.; Wenzel, O.: Causality in neuroscience. In 20th Conference of Junior Neuroscientists (NeNa 2019), W1, S. 50. 20th Conference of Junior Neuroscientists (NeNa 2019), Schramberg, Germany, 04. November 2019 - 06. November 2019. (2019)

Poster (1)

8.
Poster
Bashiri, M.; Walker, E.; Lurz, K.-K.; Jagadish, A.; Muhammad, T.; Ding, Z.; Tolias, A.; Sinz, F.: A flow-based latent state generative model of neural population responses to natural images. Bernstein Conference 2021 (2021)

Preprint (4)

9.
Preprint
Jagadish, A.; Coda-Forno, J.; Thalmann, M.; Schulz, E.; Binz, M.: Ecologically rational meta-learned inference explains human category learning. (eingereicht)
10.
Preprint
Schubert, J.; Jagadish, A.; Binz, M.; Schulz, E.: In-context learning agents are asymmetric belief updaters. (eingereicht)
11.
Preprint
Jagadish, A.; Binz, M.; Saanum, T.; Wang, J.; Schulz, E.: Zero-shot compositional reinforcement learning in humans. (eingereicht)
12.
Preprint
Coda-Forno, J.; Witte, K.; Jagadish, A.; Binz, M.; Akata, Z.; Schulz, E.: Inducing anxiety in large language models increases exploration and bias. (eingereicht)
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