Carianne Martinez

According to our database, Carianne Martinez authored at least 11 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Graph Convolutional Neural Networks as Surrogate Models for Climate Simulation.

Kevin M. Potter, Carianne Martinez, Reina Pradhan, Samantha Brozak, Steven Sleder, Lauren Wheeler

CoRR, 2024

2023

Deep sequential neural network models improve stratification of suicide attempt risk among US veterans.

Carianne Martinez, Drew Levin, Jessica Jones, Patrick D. Finley, Benjamin H. McMahon, Sayera Dhaubhadel, Judith Cohn, David W. Oslin, Nathan A. Kimbrel, Jean C. Beckham

J. Am. Medical Informatics Assoc., December, 2023

Causal disentanglement of multimodal data.

Elise Walker, Jonas A. Actor, Carianne Martinez, Nathaniel Trask

CoRR, 2023

2022

Unsupervised physics-informed disentanglement of multimodal data for high-throughput scientific discovery.

Nathaniel Trask, Carianne Martinez, Kookjin Lee, Brad Boyce

CoRR, 2022

Hierarchical partition of unity networks: fast multilevel training.

Nathaniel Trask, Amelia Henriksen, Carianne Martinez, Eric C. Cyr

Proceedings of the Mathematical and Scientific Machine Learning, 2022

2021

WiCV 2020: The Seventh Women In Computer Vision Workshop.

Hazel Doughty, Nour Karessli, Kathryn Leonard, Boyi Li, Carianne Martinez, Azadeh Mobasher, Arsha Nagrani, Srishti Yadav

CoRR, 2021

2020

Quantifying the Unknown: Impact of Segmentation Uncertainty on Image-Based Simulations.

Michael C. Krygier, Tyler LaBonte, Carianne Martinez, Chance Norris, Krish Sharma, Lincoln N. Collins, Partha P. Mukherjee, Scott A. Roberts

CoRR, 2020

Confronting Domain Shift in Trained Neural Networks.

Carianne Martinez, David A. Najera-Flores, Adam R. Brink, D. Dane Quinn, Eleni N. Chatzi, Stephanie Forrest

Proceedings of the NeurIPS 2020 Workshop on Pre-registration in Machine Learning, 2020

2019

We Know Where We Don't Know: 3D Bayesian CNNs for Uncertainty Quantification of Binary Segmentations for Material Simulations.

Tyler LaBonte, Carianne Martinez, Scott A. Roberts

CoRR, 2019

Understanding Automatically-Generated Patches Through Symbolic Invariant Differences.

Padraic Cashin, Carianne Martinez, Westley Weimer, Stephanie Forrest

Proceedings of the 34th IEEE/ACM International Conference on Automated Software Engineering, 2019

Segmentation Certainty Through Uncertainty: Uncertainty-Refined Binary Volumetric Segmentation Under Multifactor Domain Shift.

Carianne Martinez, Kevin M. Potter, Matthew D. Smith, Emily A. Donahue, Lincoln Collins, John P. Korbin, Scott A. Roberts

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, 2019