Xin Gao

Orcid: 0000-0002-1183-7223

Affiliations:
  • Beijing University of Posts and Telecommunications, School of Artificial Intelligence, China


According to our database1, Xin Gao authored at least 29 papers between 2022 and 2026.

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

Timeline

Legend:

Book  In proceedings  Article  PhD thesis  Dataset  Other 

Links

Online presence:

On csauthors.net:

Bibliography

2026
Memory-guided mask reconstruction with central contrastive learning for robust multivariate time series anomaly detection.
Neural Networks, 2026

Adaptive sample repulsion against class-specific counterfactuals for explainable imbalanced classification.
Neural Networks, 2026

Uncertainty-aware memory-enhanced cross-window dependency learning for robust multivariate time series anomaly detection.
Inf. Process. Manag., 2026

An Adversarial Filtering Framework With Time-Frequency Cross-Domain Consistency for Multivariate Time-Series Anomaly Detection.
IEEE Internet Things J., 2026

A dual-path fusion network with reconstruction and discrimination for zero-shot multivariate time series anomaly detection.
Neurocomputing, 2026

A generalized few-shot object detection method with multi-task dynamic routing and retrieval strategy of visual-semantic memory prototype.
Expert Syst. Appl., 2026

2025
Imputed-reconstruction diffusion models with negative exponential noise schedule for multivariate time series anomaly detection.
Pattern Anal. Appl., December, 2025

A meta-learning imbalanced classification framework via boundary enhancement strategy with Bayes imbalance impact index.
Neural Networks, 2025

Multivariate time series anomaly detection with heterogeneous-aware channel independence and global-local channel dependence.
Knowl. Based Syst., 2025

A multimodal data generation method for imbalanced classification with dual-discriminator constrained diffusion model and adaptive sample selection strategy.
Inf. Fusion, 2025

An adversarial transfer imbalanced classification framework via cross-category commonality information extraction and joint discrimination.
Expert Syst. Appl., 2025

A feature matching-based method for few-shot multivariate time series anomaly detection with symmetric patch mask Siam Transformer.
Eng. Appl. Artif. Intell., 2025

A dual-reconstruction self-rectification framework with momentum memory-augmented network for multivariate time series anomaly detection.
Appl. Soft Comput., 2025

2024
A filter-augmented auto-encoder with learnable normalization for robust multivariate time series anomaly detection.
Neural Networks, 2024

A robust multi-scale feature extraction framework with dual memory module for multivariate time series anomaly detection.
Neural Networks, 2024

A feature-level mask self-supervised assisted learning approach based on transformer for remaining useful life prediction.
Intell. Data Anal., 2024

An adversarial contrastive autoencoder for robust multivariate time series anomaly detection.
Expert Syst. Appl., 2024

Multivariate time series anomaly detection via separation, decomposition, and dual transformer-based autoencoder.
Appl. Soft Comput., 2024

2023
A contrastive autoencoder with multi-resolution segment-consistency discrimination for multivariate time series anomaly detection.
Appl. Intell., December, 2023

Global reliable data generation for imbalanced binary classification with latent codes reconstruction and feature repulsion.
Appl. Intell., July, 2023

Two Outlier-Sensitive Measures for Semi-supervised Dynamic Ensemble Anomaly Detection Models.
Neural Process. Lett., June, 2023

Probabilistic autoencoder with multi-scale feature extraction for multivariate time series anomaly detection.
Appl. Intell., June, 2023

An imbalanced binary classification method via space mapping using normalizing flows with class discrepancy constraints.
Inf. Sci., April, 2023

An imbalanced binary classification method based on contrastive learning using multi-label confidence comparisons within sample-neighbors pair.
Neurocomputing, 2023

2022
An ensemble-based outlier detection method for clustered and local outliers with differential potential spread loss.
Knowl. Based Syst., 2022

An ensemble contrastive classification framework for imbalanced learning with sample-neighbors pair construction.
Knowl. Based Syst., 2022

Robust outlier detection based on the changing rate of directed density ratio.
Expert Syst. Appl., 2022

Detection of local and clustered outliers based on the density-distance decision graph.
Eng. Appl. Artif. Intell., 2022

Correlation-based feature partition regression method for unsupervised anomaly detection.
Appl. Intell., 2022


  Loading...