Justin Wood

According to our database, Justin Wood authored at least 14 papers between 2015 and 2023.

Collaborative distances:

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

2023

Curriculum Learning With Infant Egocentric Videos.

Saber Sheybani, Himanshu Hansaria, Justin Wood, Linda B. Smith, Zoran Tiganj

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Surface Navigation of Alginate Artificial Cells in Mucus Solutions.

Louis William Rogowski, Justin Wood, Tobias Cooke, Gokhan Kararsiz, Min Jun Kim

IROS, 2023

2022

Knowledge discovery from biomedical and scientific text.

Justin Wood

PhD thesis, 2022

Knowledge Source Rankings for Semi-Supervised Topic Modeling.

Justin Wood, Corey W. Arnold, Wei Wang

Inf., 2022

A Bayesian Topic Model for Human-Evaluated Interpretability.

Justin Wood, Corey W. Arnold, Wei Wang

Proceedings of the Thirteenth Language Resources and Evaluation Conference, 2022

OpBerg: Discovering Causal Sentences Using Optimal Alignments.

Justin Wood, Nicholas J. Matiasz, Alcino J. Silva, William Hsu, Alexej Abyzov, Wei Wang

Proceedings of the Big Data Analytics and Knowledge Discovery, 2022

2021

Experiment Selection in Meta-Analytic Piecemeal Causal Discovery.

Nicholas J. Matiasz, Justin Wood, Wei Wang, Alcino J. Silva, William Hsu

IEEE Access, 2021

The Biased Coin Flip Process for Nonparametric Topic Modeling.

Justin Wood, Wei Wang, Corey W. Arnold

Proceedings of the 16th International Conference on Document Analysis and Recognition, 2021

2017

Computer-Aided Experiment Planning toward Causal Discovery in Neuroscience.

Nicholas J. Matiasz, Justin Wood, Wei Wang, Alcino J. Silva, William Hsu

Frontiers Neuroinformatics, 2017

Aztec: A Platform to Render Biomedical Software Findable, Accessible, Interoperable, and Reusable.

Wei Wang, Brian Bleakley, Chelsea Ju, Vincent Kyi, Patrick Tan, Howard Choi, Xinxin Huang, Yichao Zhou, Justin Wood, Ding Wang, Alex Bui, Peipei Ping

CoRR, 2017

Source-LDA: Enhancing Probabilistic Topic Models Using Prior Knowledge Sources.

Justin Wood, Patrick Tan, Wei Wang, Corey W. Arnold

Proceedings of the 33rd IEEE International Conference on Data Engineering, 2017

Translating literature into causal graphs: Toward automated experiment selection.

Nicholas J. Matiasz, Justin Wood, Wei Wang, Alcino J. Silva, William Hsu

Proceedings of the 2017 IEEE International Conference on Bioinformatics and Biomedicine, 2017

2016

Source-LDA: Enhancing probabilistic topic models using prior knowledge sources.

Justin Wood

CoRR, 2016

2015

Max-Intensity: Detecting Competitive Advertiser Communities in Sponsored Search Market.

Wenchao Yu, Ariyam Das, Justin Wood, Wei Wang, Carlo Zaniolo, Ping Luo

Proceedings of the 2015 IEEE International Conference on Data Mining, 2015