Junteng Jia

Joined

April 2020

Names

Junteng Jia (Preferred)

Emails

****@cornell.edu (Confirmed)

Personal Links

Homepage

Google Scholar

DBLP

Career & Education History

PhD student

Cornell University (cornell.edu)

2015 – 2021

Undergrad student

Nanjing university (nju.edu)

2011 – 2015

Advisors, Relations & Conflicts

PhD Advisor

Austin Benson

2018 – 2021

PhD Advisor

David Bindel

2015 – 2021

PhD Advisor

Robert DiStasio

2015 – 2018

Expertise

Graph Neural Network

2019 – 2021

Network Science

2018 – 2021

High Performance Computing

2015 – 2021

Publications

Federated Domain Adaptation for ASR with Full Self-supervision
Junteng Jia
- 15 Jan 2023
- OpenReview Archive Direct Upload
- Readers: Everyone
Multi-Head State Space Model for Sequence Modeling
Yassir Fathullah, Chunyang Wu, Yuan Shangguan, Junteng Jia, Wenhan Xiong, Jay Mahadeokar, Chunxi Liu, Yangyang Shi, Ozlem Kalinli, Mike Seltzer, Mark Gales
- Published: 01 Feb 2023, Last Modified: 13 Feb 2023
- Submitted to ICLR 2023
- Readers: Everyone
Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective
Rongzhe Wei, Haoteng Yin, Junteng Jia, Austin R. Benson, Pan Li
- Published: 31 Oct 2022, Last Modified: 08 Feb 2026
- NeurIPS 2022 Accept
- Readers: Everyone
A Unifying Generative Model for Graph Learning Algorithms: Label Propagation, Graph Convolutions, and Combinations
Junteng Jia, Austin R. Benson
- 2021 (modified: 04 Nov 2022)
- CoRR 2021
- Readers: Everyone
Residual Correlation in Graph Neural Network Regression
Junteng Jia, Austin R. Benson
- 2020 (modified: 04 Nov 2022)
- KDD 2020
- Readers: Everyone
Graph-based Semi-Supervised & Active Learning for Edge Flows.
Junteng Jia, Michael T. Schaub, Santiago Segarra, Austin R. Benson
- 2019 (modified: 09 Nov 2022)
- CoRR2019
- Readers: Everyone
Random Spatial Network Models for Core-Periphery Structure.
Junteng Jia, Austin R. Benson
- 2019 (modified: 09 Nov 2022)
- WSDM2019
- Readers: Everyone

Junteng Jia

Names

Emails

Personal Links

Career & Education History

Advisors, Relations & Conflicts

Expertise

Publications

Federated Domain Adaptation for ASR with Full Self-supervision

Multi-Head State Space Model for Sequence Modeling

Understanding Non-linearity in Graph Neural Networks from the Bayesian-Inference Perspective

A Unifying Generative Model for Graph Learning Algorithms: Label Propagation, Graph Convolutions, and Combinations

Residual Correlation in Graph Neural Network Regression

Graph-based Semi-Supervised & Active Learning for Edge Flows.

Random Spatial Network Models for Core-Periphery Structure.

Co-Authors