Carianne Martinez

11 papers A* 1Journal 7Unranked 3

Year	Rank	Type	Title / Venue / Authors
2024	J	`jnl`	Graph Convolutional Neural Networks as Surrogate Models for Climate Simulation. CoRR Kevin M. Potter, Carianne Martinez, Reina Pradhan, Samantha J. Brozak, Steven Sleder, Lauren Wheeler
2023	J	`jnl`	Causal disentanglement of multimodal data. CoRR Elise Walker, Jonas A. Actor, Carianne Martinez, Nathaniel Trask
2023	J	`jnl`	Deep sequential neural network models improve stratification of suicide attempt risk among US veterans. J. Am. Medical Informatics Assoc. 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
2022	—	`conf`	Hierarchical partition of unity networks: fast multilevel training. MSML Nathaniel Trask, Amelia Henriksen, Carianne Martinez, Eric C. Cyr
2022	J	`jnl`	Unsupervised physics-informed disentanglement of multimodal data for high-throughput scientific discovery. CoRR Nathaniel Trask, Carianne Martinez, Kookjin Lee, Brad Boyce
2021	J	`jnl`	WiCV 2020: The Seventh Women In Computer Vision Workshop. CoRR Hazel Doughty, Nour Karessli, Kathryn Leonard, Boyi Li, Carianne Martinez, Azadeh Mobasher, Arsha Nagrani, Srishti Yadav
2020	—	`conf`	Confronting Domain Shift in Trained Neural Networks. Preregister@NeurIPS Carianne Martinez, David A. Najera-Flores, Adam R. Brink, D. Dane Quinn, Eleni N. Chatzi, Stephanie Forrest
2020	J	`jnl`	Quantifying the Unknown: Impact of Segmentation Uncertainty on Image-Based Simulations. CoRR Michael C. Krygier, Tyler LaBonte, Carianne Martinez, Chance Norris, Krish Sharma, Lincoln N. Collins, Partha P. Mukherjee, Scott A. Roberts
2019	—	`conf`	Segmentation Certainty Through Uncertainty: Uncertainty-Refined Binary Volumetric Segmentation Under Multifactor Domain Shift. CVPR Workshops Carianne Martinez, Kevin M. Potter, Matthew D. Smith, Emily A. Donahue, Lincoln Collins, John P. Korbin, Scott A. Roberts
2019	A*	`conf`	Understanding Automatically-Generated Patches Through Symbolic Invariant Differences. ASE Padraic Cashin, Carianne Martinez, Westley Weimer, Stephanie Forrest
2019	J	`jnl`	We Know Where We Don't Know: 3D Bayesian CNNs for Uncertainty Quantification of Binary Segmentations for Material Simulations. CoRR Tyler LaBonte, Carianne Martinez, Scott A. Roberts