Publications

(2024). Structured flexibility in recurrent neural networks via neuromodulation. bioRxiv.
(2024). Modeling state-dependent communication between brain regions with switching nonlinear dynamical systems. The Twelfth International Conference on Learning Representations.
(2024). Modeling Latent Neural Dynamics with Gaussian Process Switching Linear Dynamical Systems. arXiv preprint arXiv:2408.03330.
(2023). Competitive integration of time and reward explains value-sensitive foraging decisions and frontal cortex ramping dynamics. bioRxiv.
(2021). Slice sampling reparameterization gradients. Advances in Neural Information Processing Systems.
(2021). Neural latents benchmark'21: evaluating latent variable models of neural population activity. arXiv preprint arXiv:2109.04463.
(2020). Modeling statistical dependencies in multi-region spike train data. Current opinion in neurobiology.
(2020). Efficient non-conjugate Gaussian process factor models for spike count data using polynomial approximations. International conference on machine learning.
(2020). A general recurrent state space framework for modeling neural dynamics during decision-making. Proceedings of the International Conference on Machine Learning (ICML).
(2019). Discrete stepping and nonlinear ramping dynamics underlie spiking responses of LIP neurons during decision-making. Neuron.