Publications
2023
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AAAISNN-PDE: Learning Dynamic PDEs from Data with Simplicial Neural NetworksIn Proceedings of the AAAI Conference on Artificial Intelligence 2023
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AAAITopoGCL: Topological Graph Contrastive LearningIn Proceedings of the AAAI Conference on Artificial Intelligence 2023
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AAAITime-Aware Knowledge Representations of Dynamic Objects with Multidimensional PersistenceIn Proceedings of the AAAI Conference on Artificial Intelligence 2023
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LOGUnited We Stand, Divided We Fall: Networks to Graph (N2G) Abstraction for Robust Graph Classification under Graph Label CorruptionIn Learning on Graphs Conference 2023
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PNASA Simplicial Epidemic Model for COVID-19 Spread AnalysisProceedings of the National Academy of Sciences 2023
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ECML-PKDDH^2-Nets: Hyper-Hodge Convolutional Neural Networks for Time-series ForecastingEuropean Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2023
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TPWRSLearning Power Grid Outages with Higher-Order Topological Neural NetworksIEEE Transactions on Power Systems 2023
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ICASSPHigher-order Spatio-temporal Neural Networks for COVID-19 ForecastingIn International Conference on Acoustics, Speech, and Signal Processing 2023
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PaKDDTopological Graph Convolutional Networks Solutions for Power Distribution Grid PlanningIn Pacific-Asia Conference on Knowledge Discovery and Data Mining 2023
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ICRAEfficient Planning of Multi-Robot Collective Transport Using Graph Reinforcement Learning with Higher Order Topological AbstractionIn IEEE International Conference on Robotics and Automation 2023
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AAAITopological Pooling on GraphsIn Proceedings of the AAAI Conference on Artificial Intelligence 2023
2022
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BigDataEvaluating Distribution System Reliability with Hyperstructures Graph Convolutional NetsIn IEEE International Conference on Big Data 2022
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BigDataLearning on Health Fairness and Environmental Justice via Interactive VisualizationIn IEEE International Conference on Big Data 2022
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NeurIPSTime Dimension Dances with Simplicial Complexes: Zigzag Filtration Curve based Supra-Hodge Convolution Networks for Time-series ForecastingIn Advances in Neural Information Processing Systems 2022
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NeurIPSToDD: Topological Compound Fingerprinting in Computer-Aided Drug DiscoveryIn Advances in Neural Information Processing Systems 2022
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ECML-PKDDTopoAttn-Nets: Topological Attention in Graph Representation LearningIn European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases 2022
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ICLRTAMP-S2GCNets: Coupling Time-Aware Multipersistence Knowledge Representation with Spatio-Supra Graph Convolutional Networks for Time-Series ForecastingIn International Conference on Learning Representations 2022
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AAAIBScNets: Block Simplicial Complex Neural NetworksIn Proceedings of the AAAI Conference on Artificial Intelligence 2022
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IAAI/AAAITCN: Pioneering Topological-based Convolutional Networks for Planetary Terrain LearningIn Proceedings of the AAAI Conference on Artificial Intelligence 2022
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PaKDDTlife-GDN: Detecting and Forecasting Spatio-Temporal Anomalies via Persistent Homology and Geometric Deep LearningIn Pacific-Asia Conference on Knowledge Discovery and Data Mining 2022
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Under revisionStability of K-means Clustering in Reproducing Kernel Hilbert SpacesUnder revision 2022
2021
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NeurIPSTopological Relational Learning on GraphsAdvances in Neural Information Processing Systems 2021
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ICMLZ-GCNETs: Time Zigzags at Graph Convolutional Networks for Time Series ForecastingIn International Conference on Machine Learning 2021
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JRSS-CUnderstanding Power Grid Network Vulnerability through the Stochastic Lens of Network Motif EvolutionInvited revision to Journal of the Royal Statistical Society: Series C 2021
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arXivUsing NASA Satellite Data Sources and Geometric Deep Learning to Uncover Hidden Patterns in COVID-19 Clinical SeverityarXiv 2021
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KDDDoes Air Quality Really Impact COVID-19 Clinical Severity: Coupling NASA Satellite Datasets with Geometric Deep LearningIn Proceedings of the 27th ACM SIGKDD Conference on Knowledge Discovery & Data Mining 2021
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IAAI/AAAIDeepening the Sense of Touch in Planetary Exploration with Geometric and Topological Deep LearningIn Proceedings of the Innovative Applications of Artificial Intelligence Conference 2021
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IAAI/AAAITopological machine learning methods for power system responses to contingenciesIn Proceedings of the Innovative Applications of Artificial Intelligence Conference 2021
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VarianceStatistical Models and Algorithms for Assessing Robustness and Reliability of Networks with Applications in Cybersecurity InsuranceVariance 2021
2020
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ICDMLFGCN: Levitating over Graphs with Levy FlightsIn International Conference on Data Mining 2020
2019
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ICDMWDeep learning Ethereum token price prediction with network motif analysisIn International Conference on Data Mining Workshops 2019
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R JournalSnowboot: bootstrap methods for network inferenceR Journal 2019
2018
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PBMBImproving the generation and selection of virtual populations in quantitative systems pharmacology modelsProgress in biophysics and molecular biology 2018
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PaKDDDeep ensemble classifiers and peer effects analysis for churn forecasting in retail bankingIn Pacific-Asia Conference on Knowledge Discovery and Data Mining 2018