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08/24/2023
Persistent learning signals and working memory without continuous attractors
Neural dynamical systems with stable attractor structures, such as point...
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06/01/2023
Linear Time GPs for Inferring Latent Trajectories from Neural Spike Trains
Latent Gaussian process (GP) models are widely used in neuroscience to u...
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05/18/2023
Real-Time Variational Method for Learning Neural Trajectory and its Dynamics
Latent variable models have become instrumental in computational neurosc...
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03/03/2023
Spectral learning of Bernoulli linear dynamical systems models for decision-making
Latent linear dynamical systems with Bernoulli observations provide a po...
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09/09/2021
Neural Latents Benchmark '21: Evaluating latent variable models of neural population activity
Advances in neural recording present increasing opportunities to study n...
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07/15/2021
Hida-Matérn Kernel
We present the class of Hida-Matérn kernels, which is the canonical fami...
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12/08/2020
On 1/n neural representation and robustness
Understanding the nature of representation in neural networks is a goal ...
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10/23/2020
Rescuing neural spike train models from bad MLE
The standard approach to fitting an autoregressive spike train model is ...
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09/02/2020
Non-parametric generalized linear model
A fundamental problem in statistical neuroscience is to model how neuron...
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06/04/2019
Streaming Variational Monte Carlo
Nonlinear state-space models are powerful tools to describe dynamical st...
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06/03/2019
Gated recurrent units viewed through the lens of continuous time dynamical systems
Gated recurrent units (GRUs) are specialized memory elements for buildin...
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11/29/2018
Tree-Structured Recurrent Switching Linear Dynamical Systems for Multi-Scale Modeling
Many real-world systems studied are governed by complex, nonlinear dynam...
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10/09/2018
Information Geometry of Orthogonal Initializations and Training
Recently mean field theory has been successfully used to analyze propert...
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07/27/2017
Recursive Variational Bayesian Dual Estimation for Nonlinear Dynamics and Non-Gaussian Observations
State space models provide an interpretable framework for complex time s...
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04/11/2016
Variational Latent Gaussian Process for Recovering Single-Trial Dynamics from Population Spike Trains
When governed by underlying low-dimensional dynamics, the interdependenc...
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11/23/2015
Black box variational inference for state space models
Latent variable time-series models are among the most heavily used tools...
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02/09/2012