Jingchao Ni

Orcid: 0000-0002-2986-6612

According to our database1, Jingchao Ni authored at least 52 papers between 2014 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2024
Interpreting Graph Neural Networks with In-Distributed Proxies.
CoRR, 2024

MELODY: Robust Semi-Supervised Hybrid Model for Entity-Level Online Anomaly Detection with Multivariate Time Series.
CoRR, 2024

2023
Hierarchical Graph Neural Networks for Causal Discovery and Root Cause Localization.
CoRR, 2023

Hierarchical Gaussian Mixture based Task Generative Model for Robust Meta-Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Interdependent Causal Networks for Root Cause Localization.
Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2023

Time Series Contrastive Learning with Information-Aware Augmentations.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
Towards Learning Disentangled Representations for Time Series.
Proceedings of the KDD '22: The 28th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, Washington, DC, USA, August 14, 2022

Superclass-Conditional Gaussian Mixture Model For Learning Fine-Grained Embeddings.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Personalized Federated Learning via Heterogeneous Modular Networks.
Proceedings of the IEEE International Conference on Data Mining, 2022

Towards Robust Graph Neural Networks via Adversarial Contrastive Learning.
Proceedings of the IEEE International Conference on Big Data, 2022

Zero-Shot Cross-Lingual Machine Reading Comprehension via Inter-sentence Dependency Graph.
Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence, 2022

2021
Do Multi-Lingual Pre-trained Language Models Reveal Consistent Token Attributions in Different Languages?
CoRR, 2021

Unsupervised Document Embedding via Contrastive Augmentation.
CoRR, 2021

Learning to Drop: Robust Graph Neural Network via Topological Denoising.
Proceedings of the WSDM '21, 2021

Deep Multi-Instance Contrastive Learning with Dual Attention for Anomaly Precursor Detection.
Proceedings of the 2021 SIAM International Conference on Data Mining, 2021

Unsupervised Concept Representation Learning for Length-Varying Text Similarity.
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, 2021

Convolutional Transformer based Dual Discriminator Generative Adversarial Networks for Video Anomaly Detection.
Proceedings of the MM '21: ACM Multimedia Conference, Virtual Event, China, October 20, 2021

Multi-Scale One-Class Recurrent Neural Networks for Discrete Event Sequence Anomaly Detection.
Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

FaceSec: A Fine-Grained Robustness Evaluation Framework for Face Recognition Systems.
Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021

Interpreting Convolutional Sequence Model by Learning Local Prototypes with Adaptation Regularization.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Structural Temporal Graph Neural Networks for Anomaly Detection in Dynamic Graphs.
Proceedings of the CIKM '21: The 30th ACM International Conference on Information and Knowledge Management, Virtual Event, Queensland, Australia, November 1, 2021

Multi-Task Recurrent Modular Networks.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

Dynamic Gaussian Mixture based Deep Generative Model For Robust Forecasting on Sparse Multivariate Time Series.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Deep Multi-Graph Clustering via Attentive Cross-Graph Association.
Proceedings of the WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, 2020

Node Classification in Temporal Graphs Through Stochastic Sparsification and Temporal Structural Convolution.
Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2020

Robust Graph Representation Learning via Neural Sparsification.
Proceedings of the 37th International Conference on Machine Learning, 2020

Inductive and Unsupervised Representation Learning on Graph Structured Objects.
Proceedings of the 8th International Conference on Learning Representations, 2020

T<sup>2</sup>-Net: A Semi-supervised Deep Model for Turbulence Forecasting.
Proceedings of the 20th IEEE International Conference on Data Mining, 2020

Deep Unsupervised Binary Coding Networks for Multivariate Time Series Retrieval.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Tensorized LSTM with Adaptive Shared Memory for Learning Trends in Multivariate Time Series.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

Asymmetrical Hierarchical Networks with Attentive Interactions for Interpretable Review-Based Recommendation.
Proceedings of the Thirty-Fourth AAAI Conference on Artificial Intelligence, 2020

2019
The multi-walker chain and its application in local community detection.
Knowl. Inf. Syst., 2019

Heterogeneous Graph Matching Networks.
CoRR, 2019

Adversarial Defense Framework for Graph Neural Network.
CoRR, 2019

Deep Co-Clustering.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Attentional Heterogeneous Graph Neural Network: Application to Program Reidentification.
Proceedings of the 2019 SIAM International Conference on Data Mining, 2019

Heterogeneous Graph Matching Networks for Unknown Malware Detection.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

Adaptive Neural Network for Node Classification in Dynamic Networks.
Proceedings of the 2019 IEEE International Conference on Data Mining, 2019

A Deep Neural Network for Unsupervised Anomaly Detection and Diagnosis in Multivariate Time Series Data.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
ComClus: A Self-Grouping Framework for Multi-Network Clustering.
IEEE Trans. Knowl. Data Eng., 2018

Deep Program Reidentification: A Graph Neural Network Solution.
CoRR, 2018

Co-Regularized Deep Multi-Network Embedding.
Proceedings of the 2018 World Wide Web Conference on World Wide Web, 2018

Local Graph Clustering by Multi-network Random Walk with Restart.
Proceedings of the Advances in Knowledge Discovery and Data Mining, 2018

2017
Ranking Causal Anomalies for System Fault Diagnosis via Temporal and Dynamical Analysis on Vanishing Correlations.
ACM Trans. Knowl. Discov. Data, 2017

Automated Medical Diagnosis by Ranking Clusters Across the Symptom-Disease Network.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Ranking Causal Anomalies by Modeling Local Propagations on Networked Systems.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Many Heads are Better than One: Local Community Detection by the Multi-walker Chain.
Proceedings of the 2017 IEEE International Conference on Data Mining, 2017

Cross-Network Clustering and Cluster Ranking for Medical Diagnosis.
Proceedings of the 33rd IEEE International Conference on Data Engineering, 2017

2016
Disease gene prioritization by integrating tissue-specific molecular networks using a robust multi-network model.
BMC Bioinform., 2016

Self-Grouping Multi-network Clustering.
Proceedings of the IEEE 16th International Conference on Data Mining, 2016

2015
Flexible and Robust Multi-Network Clustering.
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2015

2014
Inside the atoms: ranking on a network of networks.
Proceedings of the 20th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 2014


  Loading...