Brian L Trippe
Brian L Trippe
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Cited by
Cited by
Conditional density estimation with bayesian normalising flows
BL Trippe, RE Turner
arXiv preprint arXiv:1802.04908, 2018
Overpruning in variational bayesian neural networks
B Trippe, R Turner
arXiv preprint arXiv:1801.06230, 2018
The kernel interaction trick: Fast bayesian discovery of pairwise interactions in high dimensions
R Agrawal, B Trippe, J Huggins, T Broderick
International Conference on Machine Learning, 141-150, 2019
Leveraging polygenic enrichments of gene features to predict genes underlying complex traits and diseases
EM Weeks, JC Ulirsch, NY Cheng, BL Trippe, RS Fine, J Miao, ...
medRxiv, 2020
LR-GLM: High-dimensional Bayesian inference using low-rank data approximations
B Trippe, J Huggins, R Agrawal, T Broderick
International Conference on Machine Learning, 6315-6324, 2019
Inhibition of cell fate repressors secures the differentiation of the touch receptor neurons of Caenorhabditis elegans
C Zheng, FQ Jin, BL Trippe, J Wu, M Chalfie
Development 145 (22), dev168096, 2018
Neural network for processing aptamer data
MTH Dimon, M Berndl, MA Coram, B Trippe, PF Riley, PC Nelson
US Patent 10,546,650, 2020
K-mer Motif Multinomial Mixtures, a scalable framework for multiple motif discovery
BL Trippe, S Prabhakaran, HJ Bussemaker
bioRxiv, 096735, 2016
For high-dimensional hierarchical models, consider exchangeability of effects across covariates instead of across datasets
BL Trippe, HK Finucane, T Broderick
arXiv preprint arXiv:2107.06428, 2021
Optimal transport couplings of Gibbs samplers on partitions for unbiased estimation
BL Trippe, TD Nguyen, T Broderick
arXiv preprint arXiv:2104.04514, 2021
Confidently Comparing Estimators with the c-value
BL Trippe, SK Deshpande, T Broderick
arXiv preprint arXiv:2102.09705, 2021
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