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Scientific modeling applications often require estimating a distribution of parameters consistent with a dataset of observations - an inference task also known as source distribution estimation.
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Constrained Optimization and Lagrange Multiplier Methods
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Generative adversarial nets
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Adam: A method for stochastic optimization
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Sliced and Radon Wasserstein barycenters of measures
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A general framework for updating belief distributions
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Neural empirical Bayes: Source distribution estimation and its applications to simulation-based inference
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Phenotypic variation of transcriptomic cell types in mouse motor cortex
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Combined statistical-mechanistic modeling links ion channel genes to physiology of cortical neuron types
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Adversarial robustness of amortized Bayesian inference
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Methods and considerations for estimating parameters in biophysically detailed neural models with simulation based inference
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