20 citations · 83 across the 17 of their papers we have counts for
8 papers · 1 filter
Rethinking Weak Supervision in Anomaly Detection: A Comprehensive Benchmark
Xu Yao, Siyuan Zhou, Zhenbo Wu +6
Weakly supervised anomaly detection (WSAD) has developed in three primary directions: incomplete, inexact, and inaccurate supervision. However, these directions remain isolated, la…
Beyond Holistic Models: Systematic Component-level Benchmarking of Deep Multivariate Time-Series Forecasting
Shuang Liang, Chaochuan Hou, Xu Yao +4
While previous research in multivariate time series forecasting has focused on developing complex holistic models, this work advocates for a shift toward a granular, component-leve…
TSGym: Design Choices for Deep Multivariate Time-Series Forecasting
Shuang Liang, Chaochuan Hou, Xu Yao +4
Recently, deep learning has driven significant advancements in multivariate time series forecasting (MTSF) tasks. However, much of the current research in MTSF tends to evaluate mo…
Enhancing Molecular Property Prediction via Mixture of Collaborative Experts
Xu Yao, Shuang Liang, Songqiao Han +1
Molecular Property Prediction (MPP) task involves predicting biochemical properties based on molecular features, such as molecular graph structures, contributing to the discovery o…
Anomaly Detection with Score Distribution Discrimination
Minqi Jiang, Songqiao Han, Hailiang Huang
Recent studies give more attention to the anomaly detection (AD) methods that can leverage a handful of labeled anomalies along with abundant unlabeled data. These existing anomaly…
Weakly Supervised Anomaly Detection: A Survey
Minqi Jiang, Chaochuan Hou, Ao Zheng +6
Anomaly detection (AD) is a crucial task in machine learning with various applications, such as detecting emerging diseases, identifying financial frauds, and detecting fake news.…
ADBench: Anomaly Detection Benchmark
Songqiao Han, Xiyang Hu, Hailiang Huang +2
Given a long list of anomaly detection algorithms developed in the last few decades, how do they perform with regard to (i) varying levels of supervision, (ii) different types of a…
CreditPrint: Credit Investigation via Geographic Footprints by Deep Learning
Xiao Han, Ruiqing Ding, Leye Wang +1
Credit investigation is critical for financial services. Whereas, traditional methods are often restricted as the employed data hardly provide sufficient, timely and reliable infor…