David J. Schodt

According to our database, David J. Schodt authored at least 5 papers between 2021 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of three.

2024

Few-sample Variational Inference of Bayesian Neural Networks with Arbitrary Nonlinearities.

David J. Schodt

CoRR, 2024

A Framework for Variational Inference of Lightweight Bayesian Neural Networks with Heteroscedastic Uncertainties.

David J. Schodt, Ryan C. Brown, Michael Merritt, Samuel Park, Delsin Menolascino, Mark A. Peot

CoRR, 2024

2023

SMITE: Single Molecule Imaging Toolbox Extraordinaire (MATLAB).

David J. Schodt, Michael J. Wester, Mohamadreza Fazel, Sajjad Khan, Hanieh Mazloom-Farsibaf, Sandeep Pallikkuth, Marjolein B. m. Meddens, Farzin Farzam, Eric A. Burns, William K. Kanagy, Derek A. Rinaldi, Elton Jhamba, Sheng Liu, Peter K. Relich, Mark J. Olah, Stanly L. Steinberg, Keith A. Lidke

J. Open Source Softw., October, 2023

2021

Corrigendum: Spatiotemporal Clustering of Repeated Super-Resolution Localizations via Linear Assignment Problem.

David J. Schodt, Keith A. Lidke

Frontiers Bioinform., 2021

Spatiotemporal Clustering of Repeated Super-Resolution Localizations via Linear Assignment Problem.

David J. Schodt, Keith A. Lidke

Frontiers Bioinform., 2021