Hongwei Jin

52 papers A* 4A 2C 1Journal 37Unranked 8
YearRankTypeTitle / Venue / Authors
2026 J jnl
LUMINA: Foundation Models for Topology Transferable ACOPF.
CoRR
Yijiang Li, Zeeshan Memon, Hongwei Jin, Stefano Fenu, Keunju Song, Sunash B. Sharma, Parfait Gasana, Hongseok Kim, Liang Zhao, Kibaek Kim
2025 J jnl
A novel framework for dynamic and quantitative mapping of damage severity due to compound Drought-Heatwave impacts on tea Plantations, integrating Sentinel-2 and UAV images.
Comput. Electron. Agric.
Ran Huang, Yuanjun Xiao, Shengcheng Li, Jianing Li, Wei Weng, Qi Shao, Jingcheng Zhang, Yao Zhang, Lingbo Yang, Chao Huang, Weiwei Sun, Weiwei Liu, Hongwei Jin, Jingfeng Huang
2025 J jnl
A study on the 1-Γ inverse of tensors via the M-Product.
CoRR
Siran Chen, Hongwei Jin, Shaowu Huang, Julio Benítez
2025 J jnl
A study on the C-eigenvalue of the third-order tensors.
Comput. Appl. Math.
Jie Liu, Xiaoji Liu, Hongwei Jin, Hongxing Wang
2025 J jnl
Advancing anomaly detection in computational workflows with active learning.
Future Gener. Comput. Syst.
Krishnan Raghavan, George Papadimitriou, Hongwei Jin, Anirban Mandal, Mariam Kiran, Prasanna Balaprakash, Ewa Deelman
2025 — conf
Bridging Speed and Optimality in Job Scheduling: A Hybrid Ant Colony Optimization Approach for Distributed Systems.
SC Workshops
Hongwei Jin, Pawel Zuk, Krishnan Raghavan, Prachi Jadhav, Aiden Hamade, Ewa Deelman, Prasanna Balaprakash
2025 J jnl
Computing eigenvalues of third-order tensors using the C-product.
J. Appl. Math. Comput.
Hongwei Jin, Siran Chen, Jie Liu, Predrag S. Stanimirovic
2025 — conf
Evaluating the Efficacy of LLM-Based Reasoning for Multiobjective HPC Job Scheduling.
SC Workshops
Prachi Jadhav, Hongwei Jin, Ewa Deelman, Prasanna Balaprakash
2025 J jnl
Evaluating the Efficacy of LLM-Based Reasoning for Multiobjective HPC Job Scheduling.
CoRR
Prachi Jadhav, Hongwei Jin, Ewa Deelman, Prasanna Balaprakash
2025 — conf
GridMind: LLMs-Powered Agents for Power System Analysis and Operations.
SC Workshops
Hongwei Jin, Kibaek Kim, Jonghwan Kwon
2025 J jnl
GridMind: LLMs-Powered Agents for Power System Analysis and Operations.
CoRR
Hongwei Jin, Kibaek Kim, Jonghwan Kwon
2025 J jnl
On extensions of the GD inverse of tensors via the M-product.
Comput. Appl. Math.
Hongwei Jin, Siran Chen, Shaowu Huang, Predrag S. Stanimirovic
2025 J jnl
Research on a Multilayer Network Community Detection Algorithm Based on Local Information Expansion.
Big Data Min. Anal.
Xiaoming Li, Neal N. Xiong, Wei Yu, Long Chen, Hongpeng Bai, Hongwei Jin
2025 J jnl
SWARM: Reimagining scientific workflow management systems in a distributed world.
Int. J. High Perform. Comput. Appl.
Prasanna Balaprakash, Krishnan Raghavan, Franck Cappello, Ewa Deelman, Anirban Mandal, Hongwei Jin, Imtiaz Mahmud, Komal Thareja, Shixun Wu, Pawel Zuk, Mariam Kiran, Zizhong Chen, Sheng Di, Kesheng Wu
2024 J jnl
Advancing Anomaly Detection in Computational Workflows with Active Learning.
CoRR
Krishnan Raghavan, George Papadimitriou, Hongwei Jin, Anirban Mandal, Mariam Kiran, Prasanna Balaprakash, Ewa Deelman
2024 J jnl
C-S and Strongly C-S Orthogonal Matrices.
Axioms
Xiaoji Liu, Ying Liu, Hongwei Jin
2024 — conf
ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain.
GRaM
Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna, Federica Baccini, Mathilde Papillon, Miquel Ferriol-Galmés, Mustafa Hajij, Theodore Papamarkou, Maria Sofia Bucarelli, Olga Zaghen, Johan Mathe, Audun Myers, Scott Mahan, Hansen Lillemark, Sharvaree Vadgama, Erik J. Bekkers, Tim Doster, Tegan Emerson, Henry Kvinge, Katrina Agate, Nesreen K. Ahmed, Pengfei Bai, Michael Banf, Claudio Battiloro, Maxim Beketov, Paul Bogdan, Martin Carrasco, Andrea Cavallo, Yun Young Choi, George Dasoulas, Matous Elphick, Giordan Escalona, Dominik Filipiak, Halley Fritze, Thomas Gebhart, Manel Gil-Sorribes, Salvish Goomanee, Victor Guallar, Liliya Imasheva, Andrei Irimia, Hongwei Jin, Graham Johnson, Nikos Kanakaris, Boshko Koloski, Veljko Kovac, Manuel Lecha, Minho Lee, Pierrick Leroy, Theodore Long, German Magai, Alvaro Martinez, Marissa Masden, Sebastian Meznar, Bertran Miquel-Oliver, Alexis Molina, Alexander Nikitin, Marco Nurisso, Matt Piekenbrock, Yu Qin, Patryk Rygiel, Alessandro Salatiello, Max Schattauer, Pavel Snopov, Julian Suk, Valentina Sánchez, Mauricio Tec, Francesco Vaccarino, Jonas Verhellen, Frédéric Wantiez, Alexander Weers, Patrik Zajec, Blaz Skrlj, Nina Miolane
2024 J jnl
ICML Topological Deep Learning Challenge 2024: Beyond the Graph Domain.
CoRR
Guillermo Bernárdez, Lev Telyatnikov, Marco Montagna, Federica Baccini, Mathilde Papillon, Miquel Ferriol-Galmés, Mustafa Hajij, Theodore Papamarkou, Maria Sofia Bucarelli, Olga Zaghen, Johan Mathe, Audun Myers, Scott Mahan, Hansen Lillemark, Sharvaree P. Vadgama, Erik J. Bekkers, Tim Doster, Tegan Emerson, Henry Kvinge, Katrina Agate, Nesreen K. Ahmed, Pengfei Bai, Michael Banf, Claudio Battiloro, Maxim Beketov, Paul Bogdan, Martin Carrasco, Andrea Cavallo, Yun Young Choi, George Dasoulas, Matous Elphick, Giordan Escalona, Dominik Filipiak, Halley Fritze, Thomas Gebhart, Manel Gil-Sorribes, Salvish Goomanee, Victor Guallar, Liliya Imasheva, Andrei Irimia, Hongwei Jin, Graham Johnson, Nikos Kanakaris, Boshko Koloski, Veljko Kovac, Manuel Lecha, Minho Lee, Pierrick Leroy, Theodore Long, German Magai, Alvaro Martinez, Marissa Masden, Sebastian Meznar, Bertran Miquel-Oliver, Alexis Molina, Alexander Nikitin, Marco Nurisso, Matt Piekenbrock, Yu Qin, Patryk Rygiel, Alessandro Salatiello, Max Schattauer, Pavel Snopov, Julian Suk, Valentina Sánchez, Mauricio Tec, Francesco Vaccarino, Jonas Verhellen, Frédéric Wantiez, Alexander Weers, Patrik Zajec, Blaz Skrlj, Nina Miolane
2024 A conf
Large Language Models for Anomaly Detection in Computational Workflows: From Supervised Fine-Tuning to In-Context Learning.
SC
Hongwei Jin, George Papadimitriou, Krishnan Raghavan, Pawel Zuk, Prasanna Balaprakash, Cong Wang, Anirban Mandal, Ewa Deelman
2024 J jnl
Large Language Models for Anomaly Detection in Computational Workflows: from Supervised Fine-Tuning to In-Context Learning.
CoRR
Hongwei Jin, George Papadimitriou, Krishnan Raghavan, Pawel Zuk, Prasanna Balaprakash, Cong Wang, Anirban Mandal, Ewa Deelman
2024 J jnl
Latent Chemical Space Searching for Plug-in Multi-objective Molecule Generation.
CoRR
Ningfeng Liu, Jie Yu, Siyu Xiu, Xinfang Zhao, Siyu Lin, Bo Qiang, Ruqiu Zheng, Hongwei Jin, Liangren Zhang, Zhenming Liu
2024 J jnl
On the extensions of the GD inverse of tensors via the M-Product.
CoRR
Hongwei Jin, Siran Chen, Shaowu Huang, Predrag S. Stanimirovic
2024 J jnl
Physics-Informed Heterogeneous Graph Neural Networks for DC Blocker Placement.
CoRR
Hongwei Jin, Prasanna Balaprakash, Allen Zou, Pieter Ghysels, Aditi S. Krishnapriyan, Adam Mate, Arthur K. Barnes, Russell Bent
2023 J jnl
An Intelligent Prediction for the Innovation Capability of BIM Based on MSCNN-AMIGRU in Industrial Cyber Physical Systems.
IEEE Syst. J.
Hongwei Jin, Fengqin Wu
2023 J jnl
Characterizations of the Generalized MPCEP Inverse of Rectangular Matrices.
J. Appl. Math.
Jiaxuan Yao, Xiaoji Liu, Hongwei Jin
2023 J jnl
Flow-Bench: A Dataset for Computational Workflow Anomaly Detection.
CoRR
George Papadimitriou, Hongwei Jin, Cong Wang, Krishnan Raghavan, Anirban Mandal, Prasanna Balaprakash, Ewa Deelman
2023 J jnl
Graph neural networks for detecting anomalies in scientific workflows.
Int. J. High Perform. Comput. Appl.
Hongwei Jin, Krishnan Raghavan, George Papadimitriou, Cong Wang, Anirban Mandal, Mariam Kiran, Ewa Deelman, Prasanna Balaprakash
2023 J jnl
Leakage diagnosis and localization of the gas extraction pipeline based on SA-PSO BP neural network.
Reliab. Eng. Syst. Saf.
Jie Zhou, Haifei Lin, Shugang Li, Hongwei Jin, Bo Zhao, Shihao Liu
2023 J jnl
Self-supervised Learning for Anomaly Detection in Computational Workflows.
CoRR
Hongwei Jin, Krishnan Raghavan, George Papadimitriou, Cong Wang, Anirban Mandal, Ewa Deelman, Prasanna Balaprakash
2023 J jnl
The Moore-Penrose inverse of tensors via the M-product.
Comput. Appl. Math.
Hongwei Jin, Shumin Xu, Yuzhen Wang, Xiaoji Liu
2022 A* conf
Certifying Robust Graph Classification under Orthogonal Gromov-Wasserstein Threats.
NeurIPS
Hongwei Jin, Zishun Yu, Xinhua Zhang
2022 A* conf
Gromov-Wasserstein Discrepancy with Local Differential Privacy for Distributed Structural Graphs.
IJCAI
Hongwei Jin, Xun Chen
2022 J jnl
Gromov-Wasserstein Discrepancy with Local Differential Privacy for Distributed Structural Graphs.
CoRR
Hongwei Jin, Xun Chen
2022 J jnl
Orthogonal Gromov-Wasserstein Discrepancy with Efficient Lower Bound.
CoRR
Hongwei Jin, Zishun Yu, Xinhua Zhang
2022 A conf
Orthogonal Gromov-Wasserstein discrepancy with efficient lower bound.
UAI
Hongwei Jin, Zishun Yu, Xinhua Zhang
2022 — conf
Workflow Anomaly Detection with Graph Neural Networks.
WORKS@SC
Hongwei Jin, Krishnan Raghavan, George Papadimitriou, Cong Wang, Anirban Mandal, Patrycja Krawczuk, Loïc Pottier, Mariam Kiran, Ewa Deelman, Prasanna Balaprakash
2021 J jnl
A Practical Remote Sensing Monitoring Framework for Late Frost Damage in Wine Grapes Using Multi-Source Satellite Data.
Remote. Sens.
Wenjie Li, Jingfeng Huang, Lingbo Yang, Yan Chen, Yahua Fang, Hongwei Jin, Han Sun, Ran Huang
2021 J jnl
Chemical Space, Scaffolds, and Halogenated Compounds of CMNPD: A Comprehensive Chemoinformatic Analysis.
J. Chem. Inf. Model.
Ningfeng Liu, Junyong Lai, Chuanyu Lyu, Bo Qiang, Heyu Wang, Hongwei Jin, Liangren Zhang, Zhenming Liu
2020 A* conf
Certified Robustness of Graph Convolution Networks for Graph Classification under Topological Attacks.
NeurIPS
Hongwei Jin, Zhan Shi, Venkata Jaya Shankar Ashish Peruri, Xinhua Zhang
2020 — conf
Robust Training of Graph Convolutional Networks via Latent Perturbation.
ECML/PKDD (3)
Hongwei Jin, Xinhua Zhang
2020 C conf
Simulating Aggregation Algorithms for Empirical Verification of Resilient and Adaptive Federated Learning.
BDCAT
Hongwei Jin, Ning Yan, Masood S. Mortazavi
2020 J jnl
TF3P: Three-Dimensional Force Fields Fingerprint Learned by Deep Capsular Network.
J. Chem. Inf. Model.
Yanxing Wang, Jianxing Hu, Junyong Lai, Yibo Li, Hongwei Jin, Li He Zhang, Liang Ren Zhang, Zhenming Liu
2019 J jnl
TF3P: Three-dimensional Force Fields Fingerprint Learned by Deep Capsular Network.
CoRR
Yanxing Wang, Jianxing Hu, Junyong Lai, Yibo Li, Hongwei Jin, Li He Zhang, Liangren Zhang, Zhenming Liu
2018 J jnl
A universal estimation model of fractional vegetation cover for different crops based on time series digital photographs.
Comput. Electron. Agric.
Dongdong Zhang, Lamin R. Mansaray, Hongwei Jin, Han Sun, Zhaomin Kuang, Jingfeng Huang
2018 — conf
Detecting Coffee (Coffea Arabica L.) Sequential Flowering Events Based on Image Segmentation.
Agro-Geoinformatics
Huaiyue Peng, Jingfeng Huang, Hongwei Jin, Han Sun, Dengfeng Chai, Xiuzhen Wang, Bing Han, Zhen Zhou, Libing Xu
2017 J jnl
The generalized inverses of tensors and an application to linear models.
Comput. Math. Appl.
Hongwei Jin, Minru Bai, Julio Benítez, Xiaoji Liu
2014 J jnl
An Unbiased Method To Build Benchmarking Sets for Ligand-Based Virtual Screening and its Application To GPCRs.
J. Chem. Inf. Model.
Jie Xia, Hongwei Jin, Zhenming Liu, Liang Ren Zhang, Xiang Simon Wang
2013 J jnl
New Representations of the Group Inverse of 2×2 Block Matrices.
J. Appl. Math.
Xiaoji Liu, Qi Yang, Hongwei Jin
2013 J jnl
Representations of generalized inverses of partitioned matrix involving Schur complement.
Appl. Math. Comput.
Xiaoji Liu, Hongwei Jin, Dragana S. Cvetkovic-Ilic
2012 — conf
Sentiment Analysis with Multi-source Product Reviews.
ICIC (1)
Hongwei Jin, Minlie Huang, Xiaoyan Zhu
2012 J jnl
The absorption laws for the generalized inverses.
Appl. Math. Comput.
Xiaoji Liu, Hongwei Jin, Dragana S. Cvetkovic-Ilic
2011 A* conf
Incorporating Reviewer and Product Information for Review Rating Prediction.
IJCAI
Fangtao Li, Nathan Nan Liu, Hongwei Jin, Kai Zhao, Qiang Yang, Xiaoyan Zhu