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04/14/2022
SemiMultiPose: A Semi-supervised Multi-animal Pose Estimation Framework
Multi-animal pose estimation is essential for studying animals' social b...
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10/29/2020
Attentive Clustering Processes
Amortized approaches to clustering have recently received renewed attent...
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06/05/2020
A zero-inflated gamma model for deconvolved calcium imaging traces
Calcium imaging is a critical tool for measuring the activity of large n...
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04/06/2020
Disentangled sticky hierarchical Dirichlet process hidden Markov model
The Hierarchical Dirichlet Process Hidden Markov Model (HDP-HMM) has bee...
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03/11/2020
General linear-time inference for Gaussian Processes on one dimension
Gaussian Processes (GPs) provide a powerful probabilistic framework for ...
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12/28/2018
Discrete Neural Processes
Many data generating processes involve latent random variables over disc...
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11/24/2018
Amortized Bayesian inference for clustering models
We develop methods for efficient amortized approximate Bayesian inferenc...
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11/06/2018
A Novel Variational Family for Hidden Nonlinear Markov Models
Latent variable models have been widely applied for the analysis and vis...
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07/17/2018
Penalized matrix decomposition for denoising, compression, and improved demixing of functional imaging data
Calcium imaging has revolutionized systems neuroscience, providing the a...
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10/26/2017
Reparameterizing the Birkhoff Polytope for Variational Permutation Inference
Many matching, tracking, sorting, and ranking problems require probabili...
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10/26/2016
Recurrent switching linear dynamical systems
Many natural systems, such as neurons firing in the brain or basketball ...
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09/03/2016
Stochastic Bouncy Particle Sampler
We introduce a novel stochastic version of the non-reversible, rejection...
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06/24/2016
Robust and scalable Bayesian analysis of spatial neural tuning function data
A common analytical problem in neuroscience is the interpretation of neu...
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05/26/2016
Linear dynamical neural population models through nonlinear embeddings
A body of recent work in modeling neural activity focuses on recovering ...
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03/07/2016
Partition Functions from Rao-Blackwellized Tempered Sampling
Partition functions of probability distributions are important quantitie...
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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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11/13/2015
