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2020 – today
- 2024
[j27]Xiaohu Zhao
, Kebin Jia, Benjamin H. Letcher, Jennifer H. Fair, Xiaowei Jia:
Bringing vision to climate: A hierarchical model for water depth monitoring in headwater streams. Inf. Fusion 110: 102448 (2024)- [j26]Shengyu Chen, Tianshu Bao, Peyman Givi, Can Zheng, Xiaowei Jia:
Reconstructing Turbulent Flows Using Spatio-temporal Physical Dynamics. ACM Trans. Intell. Syst. Technol. 15(1): 17:1-17:18 (2024) - [j25]Erhu He, Yiqun Xie, Weiye Chen, Sergii Skakun, Han Bao, Rahul Ghosh, Praveen Ravirathinam, Xiaowei Jia:
Learning With Location-Based Fairness: A Statistically-Robust Framework and Acceleration. IEEE Trans. Knowl. Data Eng. 36(9): 4750-4765 (2024) - [j24]Daiqing Qi, Handong Zhao, Xiaowei Jia, Sheng Li:
Revealing an Overlooked Challenge in Class-Incremental Graph Learning. Trans. Mach. Learn. Res. 2024 (2024) - [c83]Weiye Chen, Yiqun Xie, Xiaowei Jia, Erhu He, Han Bao, Bang An, Xun Zhou:
Referee-Meta-Learning for Fast Adaptation of Locational Fairness. AAAI 2024: 21949-21957 - [c82]Erhu He, Yiqun Xie, Alexander Sun, Jacob Zwart, Jie Yang, Zhenong Jin, Yang Wang, Hassan A. Karimi, Xiaowei Jia:
Fair Graph Learning Using Constraint-Aware Priority Adjustment and Graph Masking in River Networks. AAAI 2024: 22087-22095 - [c81]Zhihao Wang, Yiqun Xie, Zhili Li, Xiaowei Jia, Zhe Jiang, Aolin Jia, Shuo Xu:
SimFair: Physics-Guided Fairness-Aware Learning with Simulation Models. AAAI 2024: 22420-22428 - [c80]Zelin Xu, Tingsong Xiao, Wenchong He, Yu Wang, Zhe Jiang, Shigang Chen, Yiqun Xie, Xiaowei Jia, Da Yan, Yang Zhou:
Spatial-Logic-Aware Weakly Supervised Learning for Flood Mapping on Earth Imagery. AAAI 2024: 22457-22465 - [c79]Shihong Ling, Yue Wan, Xiaowei Jia, Na Du:
Improving Explainable Object-induced Model through Uncertainty for Automated Vehicles. HRI 2024: 443-451 - [c78]Tianshu Bao, Taylor T. Johnson, Xiaowei Jia:
Transfer Learning Using Inaccurate Physics Rule for Streamflow Prediction. IJCAI 2024: 7170-7178 - [c77]Runlong Yu, Robert Ladwig, Xiang Xu, Peijun Zhu, Paul C. Hanson, Yiqun Xie, Xiaowei Jia:
Evolution-Based Feature Selection for Predicting Dissolved Oxygen Concentrations in Lakes. PPSN (4) 2024: 398-415 - [c76]Praveen Ravirathinam, Rahul Ghosh, Ankush Khandelwal, Xiaowei Jia, David J. Mulla, Vipin Kumar:
Combining Satellite and Weather Data for Crop Type Mapping: An Inverse Modelling Approach. SDM 2024: 445-453 - [c75]Mingzhi Hu, Xin Zhang, Yanhua Li, Yiqun Xie, Xiaowei Jia, Xun Zhou, Jun Luo:
Only Attending What Matter within Trajectories - Memory-Efficient Trajectory Attention. SDM 2024: 481-489 - [c74]Nasrin Kalanat, Yiqun Xie, Yanhua Li, Xiaowei Jia:
Spatial-Temporal Augmented Adaptation via Cycle-Consistent Adversarial Network: An Application in Streamflow Prediction. SDM 2024: 598-606 - [c73]Erhu He, Yiqun Xie, Licheng Liu, Zhenong Jin, Dajun Zhang, Xiaowei Jia:
Knowledge Guided Machine Learning for Extracting, Preserving, and Adapting Physics-aware Features. SDM 2024: 715-723 - [i44]Mehdi Ramezanpour, Anne M. Robertson, Yasutaka Tobe, Xiaowei Jia, Juan R. Cebral:
Phenotyping calcification in vascular tissues using artificial intelligence. CoRR abs/2401.07825 (2024) - [i43]Zhihao Wang, Yiqun Xie, Zhili Li, Xiaowei Jia, Zhe Jiang, Aolin Jia, Shuo Xu:
SimFair: Physics-Guided Fairness-Aware Learning with Simulation Models. CoRR abs/2401.15270 (2024) - [i42]Praveen Ravirathinam, Rahul Ghosh, Ankush Khandelwal, Xiaowei Jia, David J. Mulla, Vipin Kumar:
Combining Satellite and Weather Data for Crop Type Mapping: An Inverse Modelling Approach. CoRR abs/2401.15875 (2024) - [i41]Weiye Chen, Yiqun Xie, Xiaowei Jia, Erhu He, Han Bao, Bang An, Xun Zhou:
Referee-Meta-Learning for Fast Adaptation of Locational Fairness. CoRR abs/2402.13379 (2024) - [i40]Shihong Ling, Yue Wan, Xiaowei Jia, Na Du:
Improving Explainable Object-induced Model through Uncertainty for Automated Vehicles. CoRR abs/2402.15572 (2024) - [i39]Anuj Karpatne, Xiaowei Jia, Vipin Kumar:
Knowledge-guided Machine Learning: Current Trends and Future Prospects. CoRR abs/2403.15989 (2024) - [i38]Runlong Yu, Robert Ladwig, Xiang Xu, Peijun Zhu, Paul C. Hanson, Yiqun Xie, Xiaowei Jia:
Nature-Guided Cognitive Evolution for Predicting Dissolved Oxygen Concentrations in North Temperate Lakes. CoRR abs/2403.18923 (2024) - [i37]Haoran Li, Junqi Liu, Zexian Wang, Shiyuan Luo, Xiaowei Jia, Huaxiu Yao:
LITE: Modeling Environmental Ecosystems with Multimodal Large Language Models. CoRR abs/2404.01165 (2024) - [i36]Yiqun Xie, Zhihao Wang, Weiye Chen, Zhili Li, Xiaowei Jia, Yanhua Li, Ruichen Wang, Kangyang Chai, Ruohan Li, Sergii Skakun:
When are Foundation Models Effective? Understanding the Suitability for Pixel-Level Classification Using Multispectral Imagery. CoRR abs/2404.11797 (2024) - [i35]Shengyu Chen, Peyman Givi, Can Zheng, Xiaowei Jia:
Physics-enhanced Neural Operator for Simulating Turbulent Transport. CoRR abs/2406.04367 (2024) - 2023
- [j23]Xiaowei Jia, Hengbin An, Yi Hu, Zeyao Mo:
A physics-based strategy for choosing initial iterate for solving drift-diffusion equations. Comput. Math. Appl. 131: 1-13 (2023) - [j22]Tianyu Liu, Pengyu Liu, Xiaowei Jia, Shanji Chen, Ying Ma, Qian Gao:
Sea-Land Segmentation of Remote Sensing Images Based on SDW-UNet. Comput. Syst. Sci. Eng. 45(2): 1033-1045 (2023) - [j21]Jared Willard, Xiaowei Jia, Shaoming Xu, Michael S. Steinbach, Vipin Kumar:
Integrating Scientific Knowledge with Machine Learning for Engineering and Environmental Systems. ACM Comput. Surv. 55(4): 66:1-66:37 (2023) - [j20]Yiqun Xie, Weiye Chen, Erhu He, Xiaowei Jia, Han Bao, Xun Zhou, Rahul Ghosh, Praveen Ravirathinam:
Harnessing heterogeneity in space with statistically guided meta-learning. Knowl. Inf. Syst. 65(6): 2699-2729 (2023) - [j19]Shengyu Chen, Nasrin Kalanat, Yiqun Xie, Sheng Li, Jacob A. Zwart, Jeffrey M. Sadler, Alison P. Appling, Samantha K. Oliver, Jordan S. Read, Xiaowei Jia:
Physics-guided machine learning from simulated data with different physical parameters. Knowl. Inf. Syst. 65(8): 3223-3250 (2023) - [j18]Han Bao, Xun Zhou, Yiqun Xie, Yanhua Li, Xiaowei Jia:
STORM-GAN+: spatio-temporal meta-GAN for cross-city estimation of heterogeneous human mobility responses to COVID-19. Knowl. Inf. Syst. 65(11): 4759-4795 (2023) - [j17]Yang Wang, Hassan A. Karimi, Xiaowei Jia:
Reconstruction of Continuous High-Resolution Sea Surface Temperature Data Using Time-Aware Implicit Neural Representation. Remote. Sens. 15(24): 5646 (2023) - [c72]Erhu He, Yiqun Xie, Licheng Liu, Weiye Chen, Zhenong Jin, Xiaowei Jia:
Physics Guided Neural Networks for Time-Aware Fairness: An Application in Crop Yield Prediction. AAAI 2023: 14223-14231 - [c71]Zhili Li, Yiqun Xie, Xiaowei Jia, Kara Stuart, Caroline Delaire, Sergii Skakun:
Point-to-Region Co-learning for Poverty Mapping at High Resolution Using Satellite Imagery. AAAI 2023: 14321-14328 - [c70]Zhexiong Liu, Licheng Liu, Yiqun Xie, Zhenong Jin, Xiaowei Jia:
Task-Adaptive Meta-Learning Framework for Advancing Spatial Generalizability. AAAI 2023: 14365-14373 - [c69]Yiqun Xie, Zhili Li, Han Bao, Xiaowei Jia, Dongkuan Xu, Xun Zhou, Sergii Skakun:
Auto-CM: Unsupervised Deep Learning for Satellite Imagery Composition and Cloud Masking Using Spatio-Temporal Dynamics. AAAI 2023: 14575-14583 - [c68]Shengyu Chen, Nasrin Kalanat, Simon N. Topp, Jeffrey M. Sadler, Yiqun Xie, Zhe Jiang, Xiaowei Jia:
Meta-Transfer-Learning for Time Series Data with Extreme Events: An Application to Water Temperature Prediction. CIKM 2023: 266-275 - [c67]Zhihao Wang, Yiqun Xie, Xiaowei Jia, Lei Ma, George C. Hurtt:
High-Fidelity Deep Approximation of Ecosystem Simulation over Long-Term at Large Scale. SIGSPATIAL/GIS 2023: 32:1-32:10 - [c66]Yiqun Xie, Zhaonan Wang, Gengchen Mai, Yanhua Li, Xiaowei Jia, Song Gao, Shaowen Wang:
Geo-Foundation Models: Reality, Gaps and Opportunities. SIGSPATIAL/GIS 2023: 66:1-66:4 - [c65]Mingzhi Hu, Zhuoyun Zhong, Xin Zhang, Yanhua Li, Yiqun Xie, Xiaowei Jia, Xun Zhou, Jun Luo:
Self-supervised Pre-training for Robust and Generic Spatial-Temporal Representations. ICDM 2023: 150-159 - [c64]Kshitij Tayal, Arvind Renganathan, Rahul Ghosh, Xiaowei Jia, Vipin Kumar:
Koopman Invertible Autoencoder: Leveraging Forward and Backward Dynamics for Temporal Modeling. ICDM 2023: 588-597 - [c63]Erhu He, Yue Wan, Benjamin H. Letcher, Jennifer H. Fair, Yiqun Xie, Xiaowei Jia:
CGS: Coupled Growth and Survival Model with Cohort Fairness. IJCAI 2023: 5986-5994 - [c62]Zhili Li, Yiqun Xie, Xiaowei Jia:
Confidence-based Self-Corrective Learning: An Application in Height Estimation Using Satellite LiDAR and Imagery. IJCAI 2023: 6049-6057 - [c61]Shengyu Chen, Yiqun Xie, Xiang Li, Xu Liang, Xiaowei Jia:
Physics-Guided Meta-Learning Method in Baseflow Prediction over Large Regions. SDM 2023: 217-225 - [c60]Zhe Jiang, Yupu Zhang, Saugat Adhikari, Da Yan, Arpan Man Sainju, Xiaowei Jia, Yiqun Xie:
A Hidden Markov Forest Model for Terrain-Aware Flood Inundation Mapping from Earth Imagery. SDM 2023: 316-324 - [c59]Xiaowei Jia, Shengyu Chen, Can Zheng, Yiqun Xie, Zhe Jiang, Nasrin Kalanat:
Physics-guided Graph Diffusion Network for Combining Heterogeneous Simulated Data: An Application in Predicting Stream Water Temperature. SDM 2023: 361-369 - [c58]Shaoming Xu, Ankush Khandelwal, Xiang Li, Xiaowei Jia, Licheng Liu, Jared Willard, Rahul Ghosh, Kelly Cutler, Michael S. Steinbach, Christopher J. Duffy, John Nieber, Vipin Kumar:
Mini-Batch Learning Strategies for modeling long term temporal dependencies: A study in environmental applications. SDM 2023: 649-657 - [i34]Leikun Yin, Rahul Ghosh, Chenxi Lin, David Hale, Christoph Weigl, James Obarowski, Junxiong Zhou, Jessica Till, Xiaowei Jia, Troy Mao, Vipin Kumar, Zhenong Jin:
Mapping smallholder cashew plantations to inform sustainable tree crop expansion in Benin. CoRR abs/2301.00363 (2023) - [i33]Han Bao, Xun Zhou, Yiqun Xie, Yanhua Li, Xiaowei Jia:
STORM-GAN: Spatio-Temporal Meta-GAN for Cross-City Estimation of Human Mobility Responses to COVID-19. CoRR abs/2301.08648 (2023) - [i32]Rahul Ghosh, Haoyu Yang, Ankush Khandelwal, Erhu He, Arvind Renganathan, Somya Sharma, Xiaowei Jia, Vipin Kumar:
Entity Aware Modelling: A Survey. CoRR abs/2302.08406 (2023) - [i31]Shengyu Chen, Tianshu Bao, Peyman Givi, Can Zheng, Xiaowei Jia:
Reconstructing Turbulent Flows Using Physics-Aware Spatio-Temporal Dynamics and Test-Time Refinement. CoRR abs/2304.12130 (2023) - [i30]Shengyu Chen, Shihang Feng, Yao Huang, Zhou Lei, Xiaowei Jia, Youzuo Lin, Estaben Rougier:
HOSSnet: an Efficient Physics-Guided Neural Network for Simulating Crack Propagation. CoRR abs/2306.08783 (2023) - [i29]Jared D. Willard, Charuleka Varadharajan, Xiaowei Jia, Vipin Kumar:
Time Series Predictions in Unmonitored Sites: A Survey of Machine Learning Techniques in Water Resources. CoRR abs/2308.09766 (2023) - [i28]Kshitij Tayal, Arvind Renganathan, Rahul Ghosh, Xiaowei Jia, Vipin Kumar:
Koopman Invertible Autoencoder: Leveraging Forward and Backward Dynamics for Temporal Modeling. CoRR abs/2309.10291 (2023) - [i27]Yue Wan, Jialu Wu, Tingjun Hou, Chang-Yu Hsieh, Xiaowei Jia:
From molecules to scaffolds to functional groups: building context-dependent molecular representation via multi-channel learning. CoRR abs/2311.02798 (2023) - [i26]Shiyuan Luo, Juntong Ni, Shengyu Chen, Runlong Yu, Yiqun Xie, Licheng Liu, Zhenong Jin, Huaxiu Yao, Xiaowei Jia:
FREE: The Foundational Semantic Recognition for Modeling Environmental Ecosystems. CoRR abs/2311.10255 (2023) - 2022
- [j16]Zhihao Wei, Kebin Jia, Xiaowei Jia, Pengyu Liu, Ying Ma, Ting Chen, Guilian Feng:
Mapping Large-Scale Plateau Forest in Sanjiangyuan Using High-Resolution Satellite Imagery and Few-Shot Learning. Remote. Sens. 14(2): 388 (2022) - [c57]Yiqun Xie, Erhu He, Xiaowei Jia, Weiye Chen, Sergii Skakun, Han Bao, Zhe Jiang, Rahul Ghosh, Praveen Ravirathinam:
Fairness by "Where": A Statistically-Robust and Model-Agnostic Bi-level Learning Framework. AAAI 2022: 12208-12216 - [c56]Xiaohu Zhao, Kebin Jia, Benjamin H. Letcher, Jennifer H. Fair, Yiqun Xie, Xiaowei Jia:
VIMTS: Variational-based Imputation for Multi-modal Time Series. IEEE Big Data 2022: 349-358 - [c55]Rahul Ghosh, Xiaowei Jia, Leikun Yin, Chenxi Lin, Zhenong Jin, Vipin Kumar:
Clustering augmented self-supervised learning: an application to land cover mapping. SIGSPATIAL/GIS 2022: 3:1-3:10 - [c54]Erhu He, Weiye Chen, Yiqun Xie, Han Bao, Xun Zhou, Xiaowei Jia, Zhe Jiang, Rahul Ghosh, Praveen Ravirathinam:
Sailing in the location-based fairness-bias sphere. SIGSPATIAL/GIS 2022: 41:1-41:10 - [c53]Weiye Chen, Zhihao Wang, Zhili Li, Yiqun Xie, Xiaowei Jia, Anlin Li:
Deep semantic segmentation for building detection using knowledge-informed features from LiDAR point clouds. SIGSPATIAL/GIS 2022: 119:1-119:4 - [c52]Tao Wang, Pengyu Liu, Wenjing Zhang, Xiaowei Jia, Yanming Wang, Jiachun Yang:
Calibration of Multi-dimensional Air Pressure Sensor Based on LSTM. ICAIS (3) 2022: 532-543 - [c51]Han Bao, Xun Zhou, Yiqun Xie, Yanhua Li, Xiaowei Jia:
STORM-GAN: Spatio-Temporal Meta-GAN for Cross-City Estimation of Human Mobility Responses to COVID-19. ICDM 2022: 1-10 - [c50]Rahul Ghosh, Bangyan Li, Kshitij Tayal, Vipin Kumar, Xiaowei Jia:
Meta-Transfer Learning: An application to Streamflow modeling in River-streams. ICDM 2022: 161-170 - [c49]Can Zheng, Yanshan Wang, Xiaowei Jia:
Graph-Augmented Cyclic Learning Framework for Similarity Estimation of Medical Clinical Notes. ICHI 2022: 97-103 - [c48]Yiqun Xie, Erhu He, Xiaowei Jia, Han Bao, Xun Zhou, Rahul Ghosh, Praveen Ravirathinam:
Statistically-Guided Deep Network Transformation to Harness Heterogeneity in Space (Extended Abstract). IJCAI 2022: 5364-5368 - [c47]Rahul Ghosh, Arvind Renganathan, Kshitij Tayal, Xiang Li, Ankush Khandelwal, Xiaowei Jia, Christopher J. Duffy, John Nieber, Vipin Kumar:
Robust Inverse Framework using Knowledge-guided Self-Supervised Learning: An application to Hydrology. KDD 2022: 465-474 - [c46]Wenchong He, Zhe Jiang, Marcus Kriby, Yiqun Xie, Xiaowei Jia, Da Yan, Yang Zhou:
Quantifying and Reducing Registration Uncertainty of Spatial Vector Labels on Earth Imagery. KDD 2022: 554-564 - [c45]Shengyu Chen, Jacob A. Zwart, Xiaowei Jia:
Physics-Guided Graph Meta Learning for Predicting Water Temperature and Streamflow in Stream Networks. KDD 2022: 2752-2761 - [c44]Xiaowei Jia, Shengyu Chen, Yiqun Xie, Haoyu Yang, Alison P. Appling, Samantha Oliver, Zhe Jiang:
Modeling Reservoir Release Using Pseudo-Prospective Learning and Physical Simulations to Predict Water Temperature. SDM 2022: 91-99 - [c43]Kshitij Tayal, Xiaowei Jia, Rahul Ghosh, Jared Willard, Jordan S. Read, Vipin Kumar:
Invertibility aware Integration of Static and Time-series data: An application to Lake Temperature Modeling. SDM 2022: 702-710 - [c42]Tianshu Bao, Shengyu Chen, Taylor T. Johnson, Peyman Givi, Shervin Sammak, Xiaowei Jia:
Physics guided neural networks for spatio-temporal super-resolution of turbulent flows. UAI 2022: 118-128 - [i25]Xiaowei Jia, Shengyu Chen, Yiqun Xie, Haoyu Yang, Alison P. Appling, Samantha Oliver, Zhe Jiang:
Modeling Reservoir Release Using Pseudo-Prospective Learning and Physical Simulations to Predict Water Temperature. CoRR abs/2202.05714 (2022) - [i24]Can Zheng, Yanshan Wang, Xiaowei Jia:
Graph-Augmented Cyclic Learning Framework for Similarity Estimation of Medical Clinical Notes. CoRR abs/2208.09437 (2022) - [i23]Shaoming Xu, Ankush Khandelwal, Xiang Li, Xiaowei Jia, Licheng Liu, Jared Willard, Rahul Ghosh, Kelly Cutler, Michael S. Steinbach, Christopher J. Duffy, John Nieber, Vipin Kumar:
Mini-Batch Learning Strategies for modeling long term temporal dependencies: A study in environmental applications. CoRR abs/2210.08347 (2022) - [i22]Jia Li, Xiang Li, Xiaowei Jia, Michael S. Steinbach, Vipin Kumar:
Realization of Causal Representation Learning to Adjust Confounding Bias in Latent Space. CoRR abs/2211.08573 (2022) - [i21]Zhexiong Liu, Licheng Liu, Yiqun Xie, Zhenong Jin, Xiaowei Jia:
Task-Adaptive Meta-Learning Framework for Advancing Spatial Generalizability. CoRR abs/2212.06864 (2022) - 2021
- [j15]Xuan Sun, Pengyu Liu, Xiaowei Jia, Kebin Jia, Shanji Chen, Yueying Wu:
An Effective CU Depth Decision Method for HEVC Using Machine Learning. Comput. Syst. Sci. Eng. 39(2): 275-286 (2021) - [j14]Weida Zhong, Qiuling Suo, Abhishek Gupta, Xiaowei Jia, Chunming Qiao, Lu Su:
MetaTP: Traffic Prediction with Unevenly-Distributed Road Sensing Data via Fast Adaptation. Proc. ACM Interact. Mob. Wearable Ubiquitous Technol. 5(3): 141:1-141:28 (2021) - [j13]Zhihao Wei, Kebin Jia, Pengyu Liu, Xiaowei Jia, Yiqun Xie, Zhe Jiang:
Large-Scale River Mapping Using Contrastive Learning and Multi-Source Satellite Imagery. Remote. Sens. 13(15): 2893 (2021) - [j12]Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan S. Read, Jacob A. Zwart, Michael S. Steinbach, Vipin Kumar:
Physics-Guided Machine Learning for Scientific Discovery: An Application in Simulating Lake Temperature Profiles. Trans. Data Sci. 2(3): 20:1-20:26 (2021) - [j11]Yiqun Xie, Xiaowei Jia, Shashi Shekhar, Han Bao, Xun Zhou:
Significant DBSCAN+: Statistically Robust Density-based Clustering. ACM Trans. Intell. Syst. Technol. 12(5): 62:1-62:26 (2021) - [j10]Xiaowei Jia, Xiaoyi Li, Nan Du, Yuan Zhang, Vishrawas Gopalakrishnan, Guangxu Xun, Aidong Zhang:
Tracking Community Consistency in Dynamic Networks: An Influence-Based Approach. IEEE Trans. Knowl. Data Eng. 33(2): 782-795 (2021) - [c41]Shengyu Chen, Shervin Sammak, Peyman Givi, Joseph P. Yurko, Xiaowei Jia:
Reconstructing High-resolution Turbulent Flows Using Physics-Guided Neural Networks. IEEE BigData 2021: 1369-1379 - [c40]Rahul Ghosh, Praveen Ravirathinam, Xiaowei Jia, Chenxi Lin, Zhenong Jin, Vipin Kumar:
Attention-augmented Spatio-Temporal Segmentation for Land Cover Mapping. IEEE BigData 2021: 1399-1408 - [c39]Rahul Ghosh, Praveen Ravirathinam, Xiaowei Jia, Ankush Khandelwal, David J. Mulla, Vipin Kumar:
CalCROP21: A Georeferenced multi-spectral dataset of Satellite Imagery and Crop Labels. IEEE BigData 2021: 1625-1632 - [c38]Yiqun Xie, Xiaowei Jia, Han Bao, Xun Zhou, Jia Yu, Rahul Ghosh, Praveen Ravirathinam:
Spatial-Net: A Self-Adaptive and Model-Agnostic Deep Learning Framework for Spatially Heterogeneous Datasets. SIGSPATIAL/GIS 2021: 313-323 - [c37]Weida Zhong, Qiuling Suo, Xiaowei Jia, Aidong Zhang, Lu Su:
Heterogeneous Spatio-Temporal Graph Convolution Network for Traffic Forecasting with Missing Values. ICDCS 2021: 707-717 - [c36]Tianshu Bao, Xiaowei Jia, Jacob Zwart, Jeffrey M. Sadler, Alison P. Appling, Samantha Oliver, Taylor T. Johnson:
Partial Differential Equation Driven Dynamic Graph Networks for Predicting Stream Water Temperature. ICDM 2021: 11-20 - [c35]Xiaowei Jia, Yiqun Xie, Sheng Li, Shengyu Chen, Jacob Zwart, Jeffrey M. Sadler, Alison P. Appling, Samantha Oliver, Jordan S. Read:
Physics-Guided Machine Learning from Simulation Data: An Application in Modeling Lake and River Systems. ICDM 2021: 270-279 - [c34]Yiqun Xie, Erhu He, Xiaowei Jia, Han Bao, Xun Zhou, Rahul Ghosh, Praveen Ravirathinam:
A Statistically-Guided Deep Network Transformation and Moderation Framework for Data with Spatial Heterogeneity. ICDM 2021: 767-776 - [c33]Shengyu Chen, Alison P. Appling, Samantha Oliver, Hayley Corson-Dosch, Jordan S. Read, Jeffrey M. Sadler, Jacob Zwart, Xiaowei Jia:
Heterogeneous Stream-reservoir Graph Networks with Data Assimilation. ICDM 2021: 1024-1029 - [c32]Xiaowei Jia, Jacob Zwart, Jeffrey M. Sadler, Alison P. Appling, Samantha Oliver, Steven Markstrom, Jared Willard, Shaoming Xu, Michael S. Steinbach, Jordan S. Read, Vipin Kumar:
Physics-Guided Recurrent Graph Model for Predicting Flow and Temperature in River Networks. SDM 2021: 612-620 - [c31]Xiaowei Jia, Beiyu Lin, Jacob Zwart, Jeffrey M. Sadler, Alison P. Appling, Samantha Oliver, Jordan S. Read:
Graph-based Reinforcement Learning for Active Learning in Real Time: An Application in Modeling River Networks. SDM 2021: 621-629 - [i20]Rahul Ghosh, Xiaowei Jia, Vipin Kumar:
Land Cover Mapping in Limited Labels Scenario: A Survey. CoRR abs/2103.02429 (2021) - [i19]Rahul Ghosh, Praveen Ravirathinam, Xiaowei Jia, Chenxi Lin, Zhenong Jin, Vipin Kumar:
Attention-augmented Spatio-Temporal Segmentation for Land Cover Mapping. CoRR abs/2105.02963 (2021) - [i18]Rahul Ghosh, Praveen Ravirathinam, Xiaowei Jia, Ankush Khandelwal, David J. Mulla, Vipin Kumar:
CalCROP21: A Georeferenced multi-spectral dataset of Satellite Imagery and Crop Labels. CoRR abs/2107.12499 (2021) - [i17]Rahul Ghosh, Xiaowei Jia, Chenxi Lin, Zhenong Jin, Vipin Kumar:
Clustering augmented Self-Supervised Learning: Anapplication to Land Cover Mapping. CoRR abs/2108.07323 (2021) - [i16]Guruprasad Nayak, Rahul Ghosh, Xiaowei Jia, Vipin Kumar:
Weakly Supervised Classification Using Group-Level Labels. CoRR abs/2108.07330 (2021) - [i15]Shengyu Chen, Shervin Sammak, Peyman Givi, Joseph P. Yurko, Xiaowei Jia:
Reconstructing High-resolution Turbulent Flows Using Physics-Guided Neural Networks. CoRR abs/2109.03327 (2021) - [i14]Rahul Ghosh, Arvind Renganathan, Ankush Khandelwal, Xiaowei Jia, Xiang Li, John Nieber, Christopher J. Duffy, Vipin Kumar:
Knowledge-guided Self-supervised Learning for estimating River-Basin Characteristics. CoRR abs/2109.06429 (2021) - [i13]Shengyu Chen, Alison P. Appling, Samantha Oliver, Hayley Corson-Dosch, Jordan S. Read, Jeffrey M. Sadler, Jacob Zwart, Xiaowei Jia:
Heterogeneous Stream-reservoir Graph Networks with Data Assimilation. CoRR abs/2110.04959 (2021) - 2020
- [j9]Xiaowei Jia, Ankush Khandelwal, Kimberly Carlson, James Gerber, Paul C. West, Leah H. Samberg, Vipin Kumar:
Automated Plantation Mapping in Southeast Asia Using MODIS Data and Imperfect Visual Annotations. Remote. Sens. 12(4): 636 (2020) - [c30]Kshitij Tayal, Nikhil Rao, Saurabh Agarwal, Xiaowei Jia, Karthik Subbian, Vipin Kumar:
Regularized Graph Convolutional Networks for Short Text Classification. COLING (Industry) 2020: 236-242 - [c29]Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan S. Read, Jacob A. Zwart, Michael S. Steinbach, Vipin Kumar:
Process Guided Deep Learning for Modeling Physical Systems: An Application in Lake Temperature Modeling. IGARSS 2020: 3494-3496 - [c28]Xiaowei Jia, Handong Zhao, Zhe Lin, Ajinkya Kale, Vipin Kumar:
Personalized Image Retrieval with Sparse Graph Representation Learning. KDD 2020: 2735-2743 - [c27]Huaxiu Yao, Xiaowei Jia, Vipin Kumar, Zhenhui Li:
Learning with Small Data. KDD 2020: 3539-3540 - [c26]Guruprasad Nayak, Rahul Ghosh, Xiaowei Jia, Varun Mithal, Vipin Kumar:
Semi-supervised Classification using Attention-based Regularization on Coarse-resolution Data. SDM 2020: 253-261 - [i12]Guruprasad Nayak, Rahul Ghosh, Xiaowei Jia, Varun Mithal, Vipin Kumar:
Semi-supervised Classification using Attention-based Regularization on Coarse-resolution Data. CoRR abs/2001.00994 (2020) - [i11]Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan S. Read, Jacob A. Zwart, Michael S. Steinbach, Vipin Kumar:
Physics-Guided Machine Learning for Scientific Discovery: An Application in Simulating Lake Temperature Profiles. CoRR abs/2001.11086 (2020) - [i10]Jared Willard, Xiaowei Jia, Shaoming Xu, Michael S. Steinbach, Vipin Kumar:
Integrating Physics-Based Modeling with Machine Learning: A Survey. CoRR abs/2003.04919 (2020) - [i9]Xiaowei Jia, Jacob Zwart, Jeffrey M. Sadler, Alison P. Appling, Samantha Oliver, Steven Markstrom, Jared Willard, Shaoming Xu, Michael S. Steinbach, Jordan S. Read, Vipin Kumar:
Physics-Guided Recurrent Graph Networks for Predicting Flow and Temperature in River Networks. CoRR abs/2009.12575 (2020) - [i8]Xiaowei Jia, Beiyu Lin, Jacob Zwart, Jeffrey M. Sadler, Alison P. Appling, Samantha Oliver, Jordan S. Read:
Graph-based Reinforcement Learning for Active Learning in Real Time: An Application in Modeling River Networks. CoRR abs/2010.14000 (2020) - [i7]Jared D. Willard, Jordan S. Read, Alison P. Appling, Samantha K. Oliver, Xiaowei Jia, Vipin Kumar:
Predicting Water Temperature Dynamics of Unmonitored Lakes with Meta Transfer Learning. CoRR abs/2011.05369 (2020) - [i6]Jia Li, Xiaowei Jia, Haoyu Yang, Vipin Kumar, Michael S. Steinbach, György J. Simon:
Teaching deep learning causal effects improves predictive performance. CoRR abs/2011.05466 (2020) - [i5]Ankush Khandelwal, Shaoming Xu, Xiang Li, Xiaowei Jia, Michael S. Steinbach, Christopher J. Duffy, John Nieber, Vipin Kumar:
Physics Guided Machine Learning Methods for Hydrology. CoRR abs/2012.02854 (2020)
2010 – 2019
- 2019
- [j8]Xiaowei Jia, Ankush Khandelwal, Kimberly Carlson, James Gerber, Paul C. West, Vipin Kumar:
Plantation Mapping in Southeast Asia. Frontiers Big Data 2: 46 (2019) - [j7]Hengbin An, Zeyao Mo, Xiaowen Xu, Xiaowei Jia:
Operator-based preconditioning for the 2-D 3-T energy equations in radiation hydrodynamics simulations. J. Comput. Phys. 385: 51-74 (2019) - [c25]Guruprasad Nayak, Rahul Ghosh, Xiaowei Jia, Varun Mithal, Vipin Kumar:
Spatio-temporal classification at multiple resolutions using multi-view regularization. IEEE BigData 2019: 4117-4120 - [c24]Xiaowei Jia, Mengdie Wang, Ankush Khandelwal, Anuj Karpatne, Vipin Kumar:
Recurrent Generative Networks for Multi-Resolution Satellite Data: An Application in Cropland Monitoring. IJCAI 2019: 2628-2634 - [c23]Xiaowei Jia, Sheng Li, Handong Zhao, Sungchul Kim, Vipin Kumar:
Towards Robust and Discriminative Sequential Data Learning: When and How to Perform Adversarial Training? KDD 2019: 1665-1673 - [c22]Xiaowei Jia, Sheng Li, Ankush Khandelwal, Guruprasad Nayak, Anuj Karpatne, Vipin Kumar:
Spatial Context-Aware Networks for Mining Temporal Discriminative Period in Land Cover Detection. SDM 2019: 513-521 - [c21]Xiaowei Jia, Guruprasad Nayak, Ankush Khandelwal, Anuj Karpatne, Vipin Kumar:
Classifying Heterogeneous Sequential Data by Cyclic Domain Adaptation: An Application in Land Cover Detection. SDM 2019: 540-548 - [c20]Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan S. Read, Jacob Zwart, Michael S. Steinbach, Vipin Kumar:
Physics Guided RNNs for Modeling Dynamical Systems: A Case Study in Simulating Lake Temperature Profiles. SDM 2019: 558-566 - [i4]Xiaowei Jia, Ankush Khandelwal, Vipin Kumar:
Automated Monitoring Cropland Using Remote Sensing Data: Challenges and Opportunities for Machine Learning. CoRR abs/1904.04329 (2019) - 2018
- [c19]Guruprasad Nayak, Varun Mithal, Xiaowei Jia, Vipin Kumar:
Classifying Multivariate Time Series by Learning Sequence-level Discriminative Patterns. SDM 2018: 252-260 - [i3]Xiaowei Jia, Anuj Karpatne, Jared Willard, Michael S. Steinbach, Jordan S. Read, Paul C. Hanson, Hilary A. Dugan, Vipin Kumar:
Physics Guided Recurrent Neural Networks For Modeling Dynamical Systems: Application to Monitoring Water Temperature And Quality In Lakes. CoRR abs/1810.02880 (2018) - [i2]Xiaowei Jia, Jared Willard, Anuj Karpatne, Jordan S. Read, Jacob Zwart, Michael S. Steinbach, Vipin Kumar:
Physics Guided RNNs for Modeling Dynamical Systems: A Case Study in Simulating Lake Temperature Profiles. CoRR abs/1810.13075 (2018) - 2017
- [j6]Hengbin An, Xiaowei Jia, Homer F. Walker:
Anderson acceleration and application to the three-temperature energy equations. J. Comput. Phys. 347: 1-19 (2017) - [j5]Weizhu Bao, Yongyong Cai, Xiaowei Jia, Qinglin Tang:
Numerical Methods and Comparison for the Dirac Equation in the Nonrelativistic Limit Regime. J. Sci. Comput. 71(3): 1094-1134 (2017) - [j4]Guangxu Xun, Xiaowei Jia, Vishrawas Gopalakrishnan, Aidong Zhang:
A Survey on Context Learning. IEEE Trans. Knowl. Data Eng. 29(1): 38-56 (2017) - [c18]Xiaowei Jia, Yifan Hu, Ankush Khandelwal, Anuj Karpatne, Vipin Kumar:
Joint sparse auto-encoder: A semi-supervised spatio-temporal approach in mapping large-scale croplands. IEEE BigData 2017: 1173-1182 - [c17]Xiaowei Jia, Ankush Khandelwal, Guruprasad Nayak, James Gerber, Kimberly Carlson, Paul C. West, Vipin Kumar:
Incremental Dual-memory LSTM in Land Cover Prediction. KDD 2017: 867-876 - [c16]Xiaowei Jia, Ankush Khandelwal, Guruprasad Nayak, James Gerber, Kimberly Carlson, Paul C. West, Vipin Kumar:
Predict Land Covers with Transition Modeling and Incremental Learning. SDM 2017: 171-179 - [i1]Xiaowei Jia, Ankush Khandelwal, Anuj Karpatne, Vipin Kumar:
Discovery of Shifting Patterns in Sequence Classification. CoRR abs/1712.07203 (2017) - 2016
- [j3]Guangxu Xun, Xiaowei Jia, Aidong Zhang:
Detecting epileptic seizures with electroencephalogram via a context-learning model. BMC Medical Informatics Decis. Mak. 16(S-2): 70 (2016) - [j2]Weizhu Bao, Yongyong Cai, Xiaowei Jia, Qinglin Tang:
A Uniformly Accurate Multiscale Time Integrator Pseudospectral Method for the Dirac Equation in the Nonrelativistic Limit Regime. SIAM J. Numer. Anal. 54(3): 1785-1812 (2016) - [c15]Xiaowei Jia, Xiaoyi Li, Nan Du, Yuan Zhang, Vishrawas Gopalakrishnan, Guangxu Xun, Aidong Zhang:
Influence based analysis of community consistency in dynamic networks. ASONAM 2016: 1-8 - [c14]Xiaowei Jia, Xiaoyi Li, Kang Li, Vishrawas Gopalakrishnan, Guangxu Xun, Aidong Zhang:
Collaborative restricted Boltzmann machine for social event recommendation. ASONAM 2016: 402-405 - [c13]Xiaowei Jia, Ankush Khandelwal, James Gerber, Kimberly Carlson, Paul C. West, Vipin Kumar:
Learning large-scale plantation mapping from imperfect annotators. IEEE BigData 2016: 1192-1201 - [c12]Xiaowei Jia, Xi C. Chen, Anuj Karpatne, Vipin Kumar:
Identifying dynamic changes with noisy labels in spatial-temporal data: A study on large-scale water monitoring application. IEEE BigData 2016: 1328-1333 - 2015
- [j1]Nan Du, Xiaowei Jia, Jing Gao, Vishrawas Gopalakrishnan, Aidong Zhang:
Tracking Temporal Community Strength in Dynamic Networks. IEEE Trans. Knowl. Data Eng. 27(11): 3125-3137 (2015) - [c11]Nan Du, Jing Gao, Liang Ge, Vishrawas Gopalakrishnan, Xiaowei Jia, Kang Li, Aidong Zhang:
Significant Edge Detection in Target Network by Exploring Multiple Auxiliary Networks. ASONAM 2015: 210-217 - [c10]Hui Li, Xiaoyi Li, Xiaowei Jia, Murali Ramanathan, Aidong Zhang:
Bone disease prediction and phenotype discovery using feature representation over electronic health records. BCB 2015: 212-221 - [c9]Guangxu Xun, Xiaowei Jia, Aidong Zhang:
Context-learning based electroencephalogram analysis for epileptic seizure detection. BIBM 2015: 325-330 - [c8]Xiaowei Jia, Aosen Wang, Xiaoyi Li, Guangxu Xun, Wenyao Xu, Aidong Zhang:
Multi-modal learning for video recommendation based on mobile application usage. IEEE BigData 2015: 837-842 - [c7]Xiaoyi Li, Xiaowei Jia, Guangxu Xun, Aidong Zhang:
Improving EEG feature learning via synchronized facial video. IEEE BigData 2015: 843-848 - [c6]Xiaoyi Li, Xiaowei Jia, Hui Li, Houping Xiao, Jing Gao, Aidong Zhang:
DRN: Bringing Greedy Layer-Wise Training into Time Dimension. ICDM 2015: 859-864 - 2014
- [c5]Xiaowei Jia, Kang Li, Xiaoyi Li, Aidong Zhang:
A Novel Semi-Supervised Deep Learning Framework for Affective State Recognition on EEG Signals. BIBE 2014: 30-37 - [c4]Xiaowei Jia, Nan Du, Jing Gao, Aidong Zhang:
Analysis on Community Variational Trend in Dynamic Networks. CIKM 2014: 151-160 - 2013
- [c3]Yunfei Hou, Xu Li, Yunjie Zhao, Xiaowei Jia, Adel W. Sadek, Kevin F. Hulme, Chunming Qiao:
Towards efficient vacant taxis Cruising Guidance. GLOBECOM 2013: 54-59 - 2012
- [c2]Xiaowei Jia, Wei Wei, Kebin Jia:
A GPU-Based DRR Generation Method Using Cubic Window. IIH-MSP 2012: 403-406 - 2011
- [c1]Jinchao Feng, Xiaowei Jia, Kebin Jia, Chenghu Qin, Jie Tian:
Total variation regularization for bioluminescence tomography with an adaptive parameter choice approach. EMBC 2011: 3946-3949
Coauthor Index
[c76] [i42] [i39] [j21] [c64] [c58] [i34] [i32] [i29] [i28] [c55] [c50] [c47] [c43] [i23] [i22] [j12] [c40] [c39] [c32] [i20] [i19] [i18] [i17] [i16] [i14] [j9] [c30] [c29] [c28] [c27] [c26] [i12] [i11] [i10] [i9] [i7] [i6] [i5] [j8] [c25] [c24] [c23] [c22] [c21] [c20] [i4] [c19] [i3] [i2] [c18] [c17] [c16] [i1] [c13] [c12]
Samantha Oliver
aka: Samantha K. Oliver
aka: Samantha K. Oliver
Jared Willard
aka: Jared D. Willard
aka: Jared D. Willard
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