Alexander New

According to our database, Alexander New authored at least 20 papers between 2018 and 2024.

Collaborative distances:

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

2024

Equation identification for fluid flows via physics-informed neural networks.

Alexander New, Marisel Villafañe-Delgado, Charles Shugert

CoRR, 2024

Self-supervised learning for crystal property prediction via denoising.

Alexander New, Nam Q. Le, Michael J. Pekala, Christopher D. Stiles

CoRR, 2024

2023

A domain-agnostic approach for characterization of lifelong learning systems.

Megan M. Baker, Alexander New, Mario Aguilar-Simon, Ziad Al-Halah, Sébastien M. R. Arnold, Eseoghene Ben-Iwhiwhu, Andrew P. Brna, Ethan Brooks, Ryan C. Brown, Zachary Daniels, Anurag Reddy Daram, Fabien Delattre, Ryan Dellana, Eric Eaton, Haotian Fu, Kristen Grauman, Jesse Hostetler, Shariq Iqbal, Cassandra Kent, Nicholas Ketz, Soheil Kolouri, George Konidaris, Dhireesha Kudithipudi, Erik G. Learned-Miller, Seungwon Lee, Michael Littman, Sandeep Madireddy, Jorge A. Mendez, Eric Q. Nguyen, Christine D. Piatko, Praveen K. Pilly, Aswin Raghavan, Abrar Rahman, Santhosh Kumar Ramakrishnan, Neale Ratzlaff, Andrea Soltoggio, Peter Stone, Indranil Sur, Zhipeng Tang, Saket Tiwari, Kyle Vedder, Felix Wang, Zifan Xu, Angel Yanguas-Gil, Harel Yedidsion, Shangqun Yu, Gautam K. Vallabha

Neural Networks, March, 2023

Data-efficient operator learning for solving high Mach number fluid flow problems.

Noah Ford, Victor J. Leon, Honest Mrema, Jeffrey Gilbert, Alexander New

CoRR, 2023

Ensemble models outperform single model uncertainties and predictions for operator-learning of hypersonic flows.

Victor J. Leon, Noah Ford, Honest Mrema, Jeffrey Gilbert, Alexander New

CoRR, 2023

Evaluating the diversity and utility of materials proposed by generative models.

Alexander New, Michael J. Pekala, Elizabeth A. Pogue, Nam Q. Le, Janna Domenico, Christine D. Piatko, Christopher D. Stiles

CoRR, 2023

Tunable complexity benchmarks for evaluating physics-informed neural networks on coupled ordinary differential equations.

Alexander New, Benjamin Eng, Andrea C. Timm, Andrew S. Gearhart

Proceedings of the 57th Annual Conference on Information Sciences and Systems, 2023

2022

Continual learning benefits from multiple sleep mechanisms: NREM, REM, and Synaptic Downscaling.

Brian S. Robinson, Clare W. Lau, Alexander New, Shane M. Nichols, Erik C. Johnson, Michael Wolmetz, William G. Coon

CoRR, 2022

Neural Basis Functions for Accelerating Solutions to High Mach Euler Equations.

David Witman, Alexander New, Hicham Alkendry, Honest Mrema

CoRR, 2022

Curvature-informed multi-task learning for graph networks.

Alexander New, Michael J. Pekala, Nam Q. Le, Janna Domenico, Christine D. Piatko, Christopher D. Stiles

CoRR, 2022

Latent Properties of Lifelong Learning Systems.

Corban G. Rivera, Chace Ashcraft, Alexander New, James Schmidt, Gautam K. Vallabha

CoRR, 2022

L2Explorer: A Lifelong Reinforcement Learning Assessment Environment.

Erik C. Johnson, Eric Q. Nguyen, Blake Schreurs, Chigozie S. Ewulum, Chace Ashcraft, Neil M. Fendley, Megan M. Baker, Alexander New, Gautam K. Vallabha

CoRR, 2022

Lifelong Learning Metrics.

Alexander New, Megan M. Baker, Eric Q. Nguyen, Gautam K. Vallabha

CoRR, 2022

Continual learning benefits from multiple sleep stages: NREM, REM, and Synaptic Downscaling.

Brian S. Robinson, Clare W. Lau, Alexander New, Shane M. Nichols, Erik C. Johnson, Michael Wolmetz, William G. Coon

Proceedings of the International Joint Conference on Neural Networks, 2022

2020

A Precision Environment-Wide Association Study of Hypertension via Supervised Cadre Models.

Alexander New, Kristin P. Bennett

IEEE J. Biomed. Health Informatics, 2020

2019

Automating Population Health Studies Through Semantics and Statistics.

Alexander New, Miao Qi, Shruthi Chari, Sabbir M. Rashid, Oshani Seneviratne, Jamie P. McCusker, John S. Erickson, Deborah L. McGuinness, Kristin P. Bennett

Proceedings of the Joint Proceedings of the International Workshops on Sensors and Actuators on the Web, 2019

Supervised Mixture Models for Population Health.

Xiao Shou, Georgios Mavroudeas, Alexander New, Kofi Arhin, Jason Nicholas Kuruzovich, Malik Magdon-Ismail, Kristin P. Bennett

Proceedings of the 2019 IEEE International Conference on Bioinformatics and Biomedicine, 2019

Semantically-targeted analytics for reproducible scientific discovery.

Alexander New, Shruthi Chari, Miao Qi, Sabbir M. Rashid, John S. Erickson, Deborah L. McGuinness, Kristin P. Bennett

Proceedings of the Conference on Artificial Intelligence for Data Discovery and Reuse, 2019

2018

Semantically-aware population health risk analyses.

Alexander New, Sabbir M. Rashid, John S. Erickson, Deborah L. McGuinness, Kristin P. Bennett

CoRR, 2018

Cadre Modeling: Simultaneously Discovering Subpopulations and Predictive Models.

Alexander New, Curt M. Breneman, Kristin P. Bennett

Proceedings of the 2018 International Joint Conference on Neural Networks, 2018