Nathan Oken Hodas

According to our database, Nathan Oken Hodas authored at least 41 papers between 2010 and 2021.

Collaborative distances:

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

2021

Adaptive Transfer Learning: a simple but effective transfer learning.

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

CoRR, 2021

One Representation to Rule Them All: Identifying Out-of-Support Examples in Few-shot Learning with Generic Representations.

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

CoRR, 2021

Prototypical Region Proposal Networks for Few-Shot Localization and Classification.

Elliott Skomski, Aaron Tuor, Andrew Avila, Lauren A. Phillips, Zachary New, Henry Kvinge, Courtney D. Corley, Nathan O. Hodas

CoRR, 2021

Fuzzy Simplicial Networks: A Topology-Inspired Model to Improve Task Generalization in Few-shot Learning.

Henry Kvinge, Zachary New, Nico Courts, Jung H. Lee, Lauren A. Phillips, Courtney D. Corley, Aaron Tuor, Andrew Avila, Nathan O. Hodas

Proceedings of the AAAI Workshop on Meta-Learning and MetaDL Challenge, 2021

2019

Explanatory Masks for Neural Network Interpretability.

Lawrence Phillips, Garrett B. Goh, Nathan O. Hodas

CoRR, 2019

Metric-Based Few-Shot Learning for Video Action Recognition.

Chris Careaga, Brian Hutchinson, Nathan Oken Hodas, Lawrence Phillips

CoRR, 2019

Learning Deep Neural Network Representations for Koopman Operators of Nonlinear Dynamical Systems.

Enoch Yeung, Soumya Kundu, Nathan O. Hodas

Proceedings of the 2019 American Control Conference, 2019

2018

Model of cognitive dynamics predicts performance on standardized tests.

Nathan O. Hodas, Jacob S. Hunter, Stephen J. Young, Kristina Lerman

J. Comput. Soc. Sci., 2018

The Outer Product Structure of Neural Network Derivatives.

Craig Bakker, Michael J. Henry, Nathan O. Hodas

CoRR, 2018

Doing the impossible: Why neural networks can be trained at all.

Nathan O. Hodas, Panos Stinis

CoRR, 2018

Sharkzor: Interactive Deep Learning for Image Triage, Sort and Summary.

Meg Pirrung, Nathan Hilliard, Artëm Yankov, Nancy O'Brien, Paul Weidert, Courtney D. Corley, Nathan O. Hodas

CoRR, 2018

Few-Shot Learning with Metric-Agnostic Conditional Embeddings.

Nathan Hilliard, Lawrence Phillips, Scott Howland, Artëm Yankov, Courtney D. Corley, Nathan O. Hodas

CoRR, 2018

How Much Chemistry Does a Deep Neural Network Need to Know to Make Accurate Predictions?

Garrett B. Goh, Charles Siegel, Abhinav Vishnu, Nathan O. Hodas, Nathan A. Baker

Proceedings of the 2018 IEEE Winter Conference on Applications of Computer Vision, 2018

Using Rule-Based Labels for Weak Supervised Learning: A ChemNet for Transferable Chemical Property Prediction.

Garrett B. Goh, Charles Siegel, Abhinav Vishnu, Nathan Oken Hodas

Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, 2018

SHARKZOR: Human in the Loop ML for User-Defined Image Classification.

Meg Pirrung, Nathan Hilliard, Nancy O'Brien, Artëm Yankov, Court D. Corley, Nathan O. Hodas

Proceedings of the 23rd International Conference on Intelligent User Interfaces Companion, 2018

A Koopman Operator Approach for Computing and Balancing Gramians for Discrete Time Nonlinear Systems.

Enoch Yeung, Zhiyuan Liu, Nathan O. Hodas

Proceedings of the 2018 Annual American Control Conference, 2018

2017

Deep learning for computational chemistry.

Garrett B. Goh, Nathan O. Hodas, Abhinav Vishnu

J. Comput. Chem., 2017

ChemNet: A Transferable and Generalizable Deep Neural Network for Small-Molecule Property Prediction.

Garrett B. Goh, Charles Siegel, Abhinav Vishnu, Nathan O. Hodas

CoRR, 2017

SMILES2Vec: An Interpretable General-Purpose Deep Neural Network for Predicting Chemical Properties.

Garrett B. Goh, Nathan O. Hodas, Charles Siegel, Abhinav Vishnu

CoRR, 2017

Bounded Rationality in Scholarly Knowledge Discovery.

Kristina Lerman, Nathan O. Hodas, Hao Wu

CoRR, 2017

Dynamic Input Structure and Network Assembly for Few-Shot Learning.

Nathan Hilliard, Nathan O. Hodas, Courtney D. Corley

CoRR, 2017

Using Social Media to Predict the Future: A Systematic Literature Review.

Lawrence Phillips, Chase Dowling, Kyle Shaffer, Nathan Oken Hodas, Svitlana Volkova

CoRR, 2017

Chemception: A Deep Neural Network with Minimal Chemistry Knowledge Matches the Performance of Expert-developed QSAR/QSPR Models.

Garrett B. Goh, Charles Siegel, Abhinav Vishnu, Nathan Oken Hodas, Nathan A. Baker

CoRR, 2017

Will Break for Productivity: Generalized Symptoms of Cognitive Depletion.

Lyndsey Franklin, Kristina Lerman, Nathan Oken Hodas

CoRR, 2017

Understanding Cognitive Depletion in Novice NMR Analysts.

Lyndsey Franklin, Kyungsik Han, Zhuanyi Huang, Dustin Arendt, Nathan Oken Hodas

CoRR, 2017

Cognitive Depletion in the Wild: a Case Study of NMR Spectroscopy Analysis.

Lyndsey Franklin, Nathan Oken Hodas

CoRR, 2017

Intrinsic and Extrinsic Evaluation of Spatiotemporal Text Representations in Twitter Streams.

Lawrence Phillips, Kyle Shaffer, Dustin Arendt, Nathan Oken Hodas, Svitlana Volkova

Proceedings of the 2nd Workshop on Representation Learning for NLP, 2017

Assessing the Linguistic Productivity of Unsupervised Deep Neural Networks.

Lawrence Phillips, Nathan Oken Hodas

Proceedings of the 39th Annual Meeting of the Cognitive Science Society, 2017

ShapeShop: Towards Understanding Deep Learning Representations via Interactive Experimentation.

Fred Hohman, Nathan O. Hodas, Duen Horng Chau

Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems, 2017

Separating Facts from Fiction: Linguistic Models to Classify Suspicious and Trusted News Posts on Twitter.

Svitlana Volkova, Kyle Shaffer, Jin Yea Jang, Nathan Oken Hodas

Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics, 2017

2016

Mutual information for fitting deep nonlinear models.

Jacob S. Hunter, Nathan O. Hodas

CoRR, 2016

Adding Semantic Information into Data Models by Learning Domain Expertise from User Interaction.

Nathan Oken Hodas, Alex Endert

CoRR, 2016

Beyond Fine Tuning: A Modular Approach to Learning on Small Data.

Ark Anderson, Kyle Shaffer, Artëm Yankov, Courtney D. Corley, Nathan Oken Hodas

CoRR, 2016

How a User's Personality Influences Content Engagement in Social Media.

Nathan O. Hodas, Ryan Butner, Court D. Corley

Proceedings of the Social Informatics - 8th International Conference, 2016

2015

Disentangling the Lexicons of Disaster Response in Twitter.

Nathan O. Hodas, Greg Ver Steeg, Joshua J. Harrison, Satish Chikkagoudar, Eric Bell, Courtney D. Corley

Proceedings of the 24th International Conference on World Wide Web Companion, 2015

2014

Network Weirdness: Exploring the Origins of Network Paradoxes.

Farshad Kooti, Nathan Oken Hodas, Kristina Lerman

Proceedings of the Eighth International Conference on Weblogs and Social Media, 2014

2013

The Simple Rules of Social Contagion.

Nathan Oken Hodas, Kristina Lerman

CoRR, 2013

Friendship Paradox Redux: Your Friends Are More Interesting Than You.

Nathan Oken Hodas, Farshad Kooti, Kristina Lerman

Proceedings of the Seventh International Conference on Weblogs and Social Media, 2013

Attention and visibility in an information-rich world.

Nathan Oken Hodas, Kristina Lerman

Proceedings of the 2013 IEEE International Conference on Multimedia and Expo Workshops, 2013

2012

How Visibility and Divided Attention Constrain Social Contagion.

Nathan Oken Hodas, Kristina Lerman

Proceedings of the 2012 International Conference on Privacy, 2012

2010

The Quality of Oscillations in Overdamped Networks.

Nathan O. Hodas

CoRR, 2010