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05/25/2023
Revisiting Structured Variational Autoencoders
Structured variational autoencoders (SVAEs) combine probabilistic graphi...
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11/01/2021
Reverse engineering recurrent neural networks with Jacobian switching linear dynamical systems
Recurrent neural networks (RNNs) are powerful models for processing time...
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10/27/2021
Generalized Shape Metrics on Neural Representations
Understanding the operation of biological and artificial networks remain...
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03/08/2021
Statistical Neuroscience in the Single Trial Limit
Individual neurons often produce highly variable responses over nominall...
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01/20/2021
Fast deep learning correspondence for neuron tracking and identification in C.elegans using synthetic training
We present an automated method to track and identify neurons in C. elega...
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10/10/2020
Point process models for sequence detection in high-dimensional neural spike trains
Sparse sequences of neural spikes are posited to underlie aspects of wor...
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01/13/2020
Unifying and generalizing models of neural dynamics during decision-making
An open question in systems and computational neuroscience is how neural...
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10/28/2019
Poisson-Randomized Gamma Dynamical Systems
This paper presents the Poisson-randomized gamma dynamical system (PRGDS...
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12/13/2018
Dose-response modeling in high-throughput cancer drug screenings: A case study with recommendations for practitioners
Personalized cancer treatments based on the molecular profile of a patie...
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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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05/31/2017
Variational Sequential Monte Carlo
Variational inference underlies many recent advances in large scale prob...
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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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10/26/2016
Bayesian latent structure discovery from multi-neuron recordings
Neural circuits contain heterogeneous groups of neurons that differ in t...
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10/18/2016
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms
Variational inference using the reparameterization trick has enabled lar...
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06/18/2015
Dependent Multinomial Models Made Easy: Stick Breaking with the Pólya-Gamma Augmentation
Many practical modeling problems involve discrete data that are best rep...
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11/27/2014
A Nonparametric Bayesian Approach to Uncovering Rat Hippocampal Population Codes During Spatial Navigation
Rodent hippocampal population codes represent important spatial informat...
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11/14/2014
A framework for studying synaptic plasticity with neural spike train data
Learning and memory in the brain are implemented by complex, time-varyin...
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02/04/2014