Nathan O. Hodas

Publication Activity (10 Years)

Years Active: 2010-2021
Publications (10 Years): 29

Top Topics

Disaster Response

Top Venues

J. Comput. Chem.

Publications

Jung H. Lee, Henry J. Kvinge, Scott Howland, Zachary New, John Buckheit, Lauren A. Phillips, Elliott Skomski, Jessica Hibler, Courtney D. Corley, Nathan O. Hodas
Adaptive Transfer Learning: a simple but effective transfer learning. CoRR (2021)
Elliott Skomski, Aaron Tuor, Andrew Avila, Lauren A. Phillips, Zachary New, Henry Kvinge, Courtney D. Corley, Nathan O. Hodas
Prototypical Region Proposal Networks for Few-Shot Localization and Classification. CoRR (2021)
Henry Kvinge, Zachary New, Nico Courts, Jung H. Lee, Lauren A. Phillips, Courtney D. Corley, Aaron Tuor, Andrew Avila, Nathan O. Hodas
Fuzzy Simplicial Networks: A Topology-Inspired Model to Improve Task Generalization in Few-shot Learning. MetaDL@AAAI (2021)
Henry Kvinge, Scott Howland, Nico Courts, Lauren A. Phillips, John Buckheit, Zachary New, Elliott Skomski, Jung H. Lee, Sandeep Tiwari, Jessica Hibler, Courtney D. Corley, Nathan O. Hodas
One Representation to Rule Them All: Identifying Out-of-Support Examples in Few-shot Learning with Generic Representations. CoRR (2021)
Henry Kvinge, Zachary New, Nico Courts, Jung H. Lee, Lauren A. Phillips, Courtney D. Corley, Aaron Tuor, Andrew Avila, Nathan O. Hodas
Fuzzy Simplicial Networks: A Topology-Inspired Model to Improve Task Generalization in Few-shot Learning. CoRR (2020)
Lawrence Phillips, Garrett B. Goh, Nathan O. Hodas
Explanatory Masks for Neural Network Interpretability. CoRR (2019)
Enoch Yeung, Soumya Kundu, Nathan O. Hodas
Learning Deep Neural Network Representations for Koopman Operators of Nonlinear Dynamical Systems. ACC (2019)
Nathan O. Hodas, Jacob S. Hunter, Stephen J. Young, Kristina Lerman
Model of Cognitive Dynamics Predicts Performance on Standardized Tests. CoRR (2018)
Nathan O. Hodas, Jacob S. Hunter, Stephen J. Young, Kristina Lerman
Model of cognitive dynamics predicts performance on standardized tests. J. Comput. Soc. Sci. 1 (2) (2018)
Enoch Yeung, Zhiyuan Liu, Nathan O. Hodas
A Koopman Operator Approach for Computing and Balancing Gramians for Discrete Time Nonlinear Systems. ACC (2018)
Nathan Hilliard, Lawrence Phillips, Scott Howland, Artëm Yankov, Courtney D. Corley, Nathan O. Hodas
Few-Shot Learning with Metric-Agnostic Conditional Embeddings. CoRR (2018)
Meg Pirrung, Nathan Hilliard, Artëm Yankov, Nancy O'Brien, Paul Weidert, Courtney D. Corley, Nathan O. Hodas
Sharkzor: Interactive Deep Learning for Image Triage, Sort and Summary. CoRR (2018)
Craig Bakker, Michael J. Henry, Nathan O. Hodas
The Outer Product Structure of Neural Network Derivatives. CoRR (2018)
Nathan O. Hodas, Panos Stinis
Doing the impossible: Why neural networks can be trained at all. CoRR (2018)
Garrett B. Goh, Charles Siegel, Abhinav Vishnu, Nathan O. Hodas, Nathan Baker
How Much Chemistry Does a Deep Neural Network Need to Know to Make Accurate Predictions? WACV (2018)
Meg Pirrung, Nathan Hilliard, Nancy O'Brien, Artëm Yankov, Court D. Corley, Nathan O. Hodas
SHARKZOR: Human in the Loop ML for User-Defined Image Classification. IUI Companion (2018)
Garrett B. Goh, Charles Siegel, Abhinav Vishnu, Nathan O. Hodas, Nathan Baker
How Much Chemistry Does a Deep Neural Network Need to Know to Make Accurate Predictions? CoRR (2017)
Garrett B. Goh, Nathan O. Hodas, Abhinav Vishnu
Deep Learning for Computational Chemistry. CoRR (2017)
Garrett B. Goh, Nathan O. Hodas, Abhinav Vishnu
Deep learning for computational chemistry. J. Comput. Chem. 38 (16) (2017)
Nathan Hilliard, Nathan O. Hodas, Courtney D. Corley
Dynamic Input Structure and Network Assembly for Few-Shot Learning. CoRR (2017)
Kristina Lerman, Nathan O. Hodas, Hao Wu
Bounded Rationality in Scholarly Knowledge Discovery. CoRR (2017)
Garrett B. Goh, Charles Siegel, Abhinav Vishnu, Nathan O. Hodas
ChemNet: A Transferable and Generalizable Deep Neural Network for Small-Molecule Property Prediction. CoRR (2017)
Enoch Yeung, Zhiyuan Liu, Nathan O. Hodas
A Koopman Operator Approach for Computing and Balancing Gramians for Discrete Time Nonlinear Systems. CoRR (2017)
Enoch Yeung, Soumya Kundu, Nathan O. Hodas
Learning Deep Neural Network Representations for Koopman Operators of Nonlinear Dynamical Systems. CoRR (2017)
Fred Hohman, Nathan O. Hodas, Duen Horng Chau
ShapeShop: Towards Understanding Deep Learning Representations via Interactive Experimentation. CHI Extended Abstracts (2017)
Garrett B. Goh, Nathan O. Hodas, Charles Siegel, Abhinav Vishnu
SMILES2Vec: An Interpretable General-Purpose Deep Neural Network for Predicting Chemical Properties. CoRR (2017)
Jacob S. Hunter, Nathan O. Hodas
Mutual information for fitting deep nonlinear models. CoRR (2016)
Nathan O. Hodas, Ryan Butner, Courtney D. Corley
How a user's personality influences content engagement in social media. CoRR (2016)
Nathan O. Hodas, Ryan Butner, Court D. Corley
How a User's Personality Influences Content Engagement in Social Media. SocInfo (1) (2016)
Nathan O. Hodas, Greg Ver Steeg, Joshua J. Harrison, Satish Chikkagoudar, Eric Bell, Courtney D. Corley
Disentangling the Lexicons of Disaster Response in Twitter. WWW (Companion Volume) (2015)
Nathan O. Hodas
The Quality of Oscillations in Overdamped Networks. CoRR (2010)