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06/24/2023
Learned Mappings for Targeted Free Energy Perturbation between Peptide Conformations
Targeted free energy perturbation uses an invertible mapping to promote ...
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04/18/2023
Bayesian D-Optimal Design of Experiments with Quantitative and Qualitative Responses
Systems with both quantitative and qualitative responses are widely enco...
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09/26/2022
Sampling Constrained Continuous Probability Distributions: A Review
The problem of sampling constrained continuous distributions has frequen...
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11/21/2021
Low-Discrepancy Points via Energetic Variational Inference
In this paper, we propose a deterministic variational inference approach...
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02/18/2021
A Generative Approach to Joint Modeling of Quantitative and Qualitative Responses
In many scientific areas, data with quantitative and qualitative (QQ) re...
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08/14/2020
Bayesian Auxiliary Variable Model for Birth Records Data with Qualitative and Quantitative Responses
Many applications involve data with qualitative and quantitative respons...
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08/14/2020
Optimal Design for A/B Testing in the Presence of Covariates and Network Connection
A/B testing, also known as controlled experiments, refers to the statist...
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08/14/2020
A Maximin Φ_p-Efficient Design for Multivariate GLM
Experimental designs for a generalized linear model (GLM) often depend o...
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08/12/2020
Covariate Balancing Based on Kernel Density Estimates for Controlled Experiments
Controlled experiments are widely used in many applications to investiga...
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04/21/2020
Is a Transformed Low Discrepancy Design Also Low Discrepancy?
Experimental designs intended to match arbitrary target distributions ar...
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04/14/2020
Particle-based Energetic Variational Inference
We introduce a new variational inference framework, called energetic var...
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10/07/2019
Gaussian Process Assisted Active Learning of Physical Laws
In many areas of science and engineering, discovering the governing diff...
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02/01/2019
D-optimal Design for Network A/B Testing
A/B testing refers to the statistical procedure of conducting an experim...
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01/25/2019