| A tensor decomposition-based approach for detecting dynamic network states from EEG AG Mahyari, DM Zoltowski, EM Bernat, S Aviyente IEEE Transactions on Biomedical Engineering 64 (1), 225-237, 2016 | 69 | 2016 |
| Neural latents benchmark'21: evaluating latent variable models of neural population activity F Pei, J Ye, D Zoltowski, A Wu, RH Chowdhury, H Sohn, JE O'Doherty, ... arXiv preprint arXiv:2109.04463, 2021 | 63 | 2021 |
| Discrete stepping and nonlinear ramping dynamics underlie spiking responses of LIP neurons during decision-making DM Zoltowski, KW Latimer, JL Yates, AC Huk, JW Pillow Neuron 102 (6), 1249-1258. e10, 2019 | 50 | 2019 |
| A general recurrent state space framework for modeling neural dynamics during decision-making DM Zoltowski, JW Pillow, SW Linderman Proceedings of the International Conference on Machine Learning (ICML), 2983 …, 2020 | 40 | 2020 |
| Modeling statistical dependencies in multi-region spike train data SL Keeley, DM Zoltowski, MC Aoi, JW Pillow Current opinion in neurobiology 65, 194-202, 2020 | 37 | 2020 |
| Scaling the Poisson GLM to massive neural datasets through polynomial approximations DM Zoltowski, JW Pillow Advances in Neural Information Processing Systems, 3521-3531, 2018 | 27 | 2018 |
| Efficient non-conjugate Gaussian process factor models for spike count data using polynomial approximations S Keeley, D Zoltowski, Y Yu, S Smith, J Pillow International conference on machine learning, 5177-5186, 2020 | 20 | 2020 |
| Sparsity-promoting optimal control of spatially-invariant systems DM Zoltowski, N Dhingra, F Lin, MR Jovanović 2014 American Control Conference, 1255-1260, 2014 | 20 | 2014 |
| SSM: Bayesian learning and inference for state space models S Linderman, B Antin, D Zoltowski, J Glaser Oct, 2020 | 17 | 2020 |
| A graph theoretic approach to dynamic functional connectivity tracking and network state identification DM Zoltowski, EM Bernat, S Aviyente 2014 36th Annual International Conference of the IEEE Engineering in …, 2014 | 9 | 2014 |
| Unifying and generalizing models of neural dynamics during decision-making DM Zoltowski, JW Pillow, SW Linderman arXiv preprint arXiv:2001.04571, 2020 | 7 | 2020 |
| Slice sampling reparameterization gradients D Zoltowski, D Cai, RP Adams Advances in Neural Information Processing Systems 34, 23532-23544, 2021 | 5 | 2021 |
| Low-rank tensor decomposition based dynamic network tracking DM Zoltowski, S Aviyente 2014 IEEE Global Conference on Signal and Information Processing (GlobalSIP …, 2014 | 3 | 2014 |
| Modeling communication and switching nonlinear dynamics in multi-region neural activity O Karniol-Tambour, DM Zoltowski, EM Diamanti, L Pinto, DW Tank, ... bioRxiv, 2022.09. 13.507841, 2022 | 1 | 2022 |
| Modeling state-dependent communication between brain regions with switching nonlinear dynamical systems O Karniol-Tambour, DM Zoltowski, EM Diamanti, L Pinto, CD Brody, ... The Twelfth International Conference on Learning Representations, 2023 | | 2023 |
| Competitive integration of time and reward explains value-sensitive foraging decisions and frontal cortex ramping dynamics M Bukwich, MG Campbell, D Zoltowski, L Kingsbury, MS Tomov, J Stern, ... bioRxiv, 2023 | | 2023 |
| Probabilistic Methods for Modeling Decision-Making Dynamics and Identifying Structure in Neural Datasets DM Zoltowski Princeton University, 2022 | | 2022 |
| Supplementary Material: Slice Sampling Reparameterization Gradients DM Zoltowski, D Cai, RP Adams | | |
Jonathan PillowProfessor of Neuroscience, Princeton University在 princeton.edu 的电子邮件经过验证
