Tansey, W., Li, K., Zhang, H., Linderman, S. W., Rabadan, R., Blei, D. M., & Wiggins, C. H. (2018). Dose-response modeling in high-throughput cancer drug screenings: A case study with recommendations for practitioners. *ArXiv Preprint ArXiv:1812.05691*.
arXiv
Sharma, A., Johnson, R. E., Engert, F., & Linderman, S. W. (2018). Point process latent variable models of freely swimming larval zebrafish. *Advances in Neural Information Processing Systems (NeurIPS)*.
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Markowitz, J. E., Gillis, W. F., Beron, C. C., Neufeld, S. Q., Robertson, K., Bhagat, N. D., … Datta, S. R. (2018). The Striatum Organizes 3D Behavior via Moment-to-Moment Action Selection. *Cell*. https://doi.org/doi: 10.1016/j.cell.2018.04.019
Paper
Linderman, S. W., Nichols, A., Blei, D. M., Zimmer, M., & Paninski, L. (2018). Hierarchical recurrent models reveal latent states of neural activity in C. elegans. *Computational and Systems Neuroscience (Cosyne) Abstracts*.

Markowitz, J. E., Gillis, W. F., Beron, C. C., Neufeld, S. Q., Robertson, K., Bhagat, N. D., … Datta, S. R. (2018). Complementary Direct and Indirect Pathway Activity Encodes Sub-Second 3D Pose Dynamics in Striatum. *Computational and Systems Neuroscience (Cosyne) Abstracts*.

Johnson*, R. E., Linderman*, S. W., Panier, T., Wee, C., Song, E., Herrera, K., … Engert, F. (2018). Revealing multiple timescales of structure in larval zebrafish behavior. *Computational and Systems Neuroscience (Cosyne) Abstracts*.

Mena, G. E., Belanger, D., Linderman, S. W., & Snoek, J. (2018). Learning Latent Permutations with Gumbel-Sinkhorn Networks. *International Conference on Learning Representations (ICLR)*.
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Linderman, S. W., Mena, G. E., Cooper, H., Paninski, L., & Cunningham, J. P. (2018). Reparameterizing the Birkhoff Polytope for Variational Permutation Inference. In *Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS)*.
Paper
arXiv
Naesseth, C. A., Linderman, S. W., Ranganath, R., & Blei, D. M. (2018). Variational Sequential Monte Carlo. In *Proceedings of the 21st International Conference on Artificial Intelligence and Statistics (AISTATS)*.
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arXiv
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