Weiwei Yang

According to our database, Weiwei Yang authored at least 16 papers between 2020 and 2025.

Collaborative distances:

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

2025

Simple Lifelong Learning Machines.

Joshua T. Vogelstein, Jayanta Dey, Hayden S. Helm, Will LeVine, Ronak D. Mehta, Tyler M. Tomita, Haoyin Xu, Ali Geisa, Qingyang Wang, Gido M. van de Ven, Chenyu Gao, Weiwei Yang, Bryan Tower, Jonathan Larson, Christopher M. White, Carey E. Priebe

IEEE Trans. Pattern Anal. Mach. Intell., November, 2025

Multiple network embedding for anomaly detection in time series of graphs.

Guodong Chen, Jesús Arroyo, Avanti Athreya, Joshua Cape, Joshua T. Vogelstein, Youngser Park, Christopher M. White, Jonathan Larson, Weiwei Yang, Carey E. Priebe

Comput. Stat. Data Anal., 2025

2023

Discovering a change point and piecewise linear structure in a time series of organoid networks via the iso-mirror.

Tianyi Chen, Youngser Park, Ali Saad-Eldin, Zachary Lubberts, Avanti Athreya, Benjamin D. Pedigo, Joshua T. Vogelstein, Francesca Puppo, Gabriel A. Silva, Alysson R. Muotri, Weiwei Yang, Christopher M. White, Carey E. Priebe

Appl. Netw. Sci., December, 2023

Distance-based positive and unlabeled learning for ranking.

Hayden S. Helm, Amitabh Basu, Avanti Athreya, Youngser Park, Joshua T. Vogelstein, Carey E. Priebe, Michael Winding, Marta Zlatic, Albert Cardona, Patrick Bourke, Jonathan Larson, Marah Ihab Abdin, Piali Choudhury, Weiwei Yang, Christopher M. White

Pattern Recognit., 2023

A Statistical Turing Test for Generative Models.

Hayden S. Helm, Carey E. Priebe, Weiwei Yang

CoRR, 2023

Approximately optimal domain adaptation with Fisher's Linear Discriminant Analysis.

Hayden S. Helm, Weiwei Yang, Ashwin De Silva, Joshua T. Vogelstein, Carey E. Priebe

CoRR, 2023

Towards closing the data gap: A project-driven distributed energy resource dataset for the U.S. Grid.

Rabab Haider, Yixing Xu, Weiwei Yang

Proceedings of the Companion Proceedings of the 14th ACM International Conference on Future Energy Systems, 2023

Prospective Learning: Principled Extrapolation to the Future.

Ashwin De Silva, Rahul Ramesh, Lyle H. Ungar, Marshall G. Hussain Shuler, Noah J. Cowan, Michael L. Platt, Chen Li, Leyla Isik, Seung-Eon Roh, Adam S. Charles, Archana Venkataraman, Brian Caffo, Javier J. How, Justus M. Kebschull, John W. Krakauer, Maxim Bichuch, Kaleab Alemayehu Kinfu, Eva Yezerets, Dinesh Jayaraman, Jong M. Shin, Soledad Villar, Ian Phillips, Carey E. Priebe, Thomas Hartung, Michael I. Miller, Jayanta Dey, Ningyuan Huang, Eric Eaton, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Randal C. Burns, Onyema Osuagwu, Brett Mensh, Alysson R. Muotri, Julia Brown, Chris White, Weiwei Yang, Andrei A. Rusu, Timothy D. Verstynen, Konrad P. Kording, Pratik Chaudhari, Joshua T. Vogelstein

Proceedings of the Conference on Lifelong Learning Agents, 2023

2022

Deep Learning with Label Noise: A Hierarchical Approach.

Li Chen, Ningyuan Huang, Cong Mu, Hayden S. Helm, Kate Lytvynets, Weiwei Yang, Carey E. Priebe

CoRR, 2022

Mental State Classification Using Multi-graph Features.

Guodong Chen, Hayden S. Helm, Kate Lytvynets, Weiwei Yang, Carey E. Priebe

CoRR, 2022

Prospective Learning: Back to the Future.

Joshua T. Vogelstein, Timothy D. Verstynen, Konrad P. Kording, Leyla Isik, John W. Krakauer, Ralph Etienne-Cummings, Elizabeth L. Ogburn, Carey E. Priebe, Randal C. Burns, Kwame S. Kutten, James J. Knierim, James B. Potash, Thomas Hartung, Lena Smirnova, Paul Worley, Alena V. Savonenko, Ian Phillips, Michael I. Miller, René Vidal, Jeremias Sulam, Adam S. Charles, Noah J. Cowan, Maxim Bichuch, Archana Venkataraman, Chen Li, Nitish V. Thakor, Justus M. Kebschull, Marilyn S. Albert, Jinchong Xu, Marshall G. Hussain Shuler, Brian Caffo, J. Tilak Ratnanather, Ali Geisa, Seung-Eon Roh, Eva Yezerets, Meghana Madhyastha, Javier J. How, Tyler M. Tomita, Jayanta Dey, Ningyuan Huang, Jong M. Shin, Kaleab Alemayehu Kinfu, Pratik Chaudhari, Ben Baker, Anna Schapiro, Dinesh Jayaraman, Eric Eaton, Michael L. Platt, Lyle H. Ungar, Leila Wehbe, Ádám Kepecs, Amy Christensen, Onyema Osuagwu, Bing Brunton, Brett Mensh, Alysson R. Muotri, Gabriel A. Silva, Francesca Puppo, Florian Engert, Elizabeth Hillman, Julia Brown, Chris White, Weiwei Yang

CoRR, 2022

2021

Leveraging semantically similar queries for ranking via combining representations.

Hayden S. Helm, Marah Ihab Abdin, Benjamin D. Pedigo, Shweti Mahajan, Vince Lyzinski, Youngser Park, Amitabh Basu, Piali Choudhury, Christopher M. White, Weiwei Yang, Carey E. Priebe

CoRR, 2021

Inducing a hierarchy for multi-class classification problems.

Hayden S. Helm, Weiwei Yang, Sujeeth Bharadwaj, Kate Lytvynets, Oriana Riva, Christopher M. White, Ali Geisa, Carey E. Priebe

CoRR, 2021

2020

A partition-based similarity for classification distributions.

Hayden S. Helm, Ronak D. Mehta, Brandon Duderstadt, Weiwei Yang, Christopher M. White, Ali Geisa, Joshua T. Vogelstein, Carey E. Priebe

CoRR, 2020

Design of a Privacy-Preserving Data Platform for Collaboration Against Human Trafficking.

Darren Edge, Weiwei Yang, Harry Cook, Claire Galez-Davis, Hannah Darnton, Kate Lytvynets, Christopher M. White

CoRR, 2020

A general approach to progressive intelligence.

Joshua T. Vogelstein, Hayden S. Helm, Ronak D. Mehta, Jayanta Dey, Weiwei Yang, Bryan Tower, Will LeVine, Jonathan Larson, Christopher M. White, Carey E. Priebe

CoRR, 2020