4 papers · 1 filter
Beyond MSE: Ordinal Cross-Entropy for Probabilistic Time Series Forecasting
Jieting Wang, Huimei Shi, Feijiang Li +1
Time series forecasting is an important task that involves analyzing temporal dependencies and underlying patterns (such as trends, cyclicality, and seasonality) in historical data…
RI-Loss: A Learnable Residual-Informed Loss for Time Series Forecasting
Jieting Wang, Xiaolei Shang, Feijiang Li +1
Time series forecasting relies on predicting future values from historical data, yet most state-of-the-art approaches-including transformer and multilayer perceptron-based models-o…
Ranked Set Sampling-Based Multilayer Perceptron: Improving Generalization via Variance-Based Bounds
Feijiang Li, Liuya Zhang, Jieting Wang +2
Multilayer perceptron (MLP), one of the most fundamental neural networks, is extensively utilized for classification and regression tasks. In this paper, we establish a new general…
Hybrid Causal Identification and Causal Mechanism Clustering
Saixiong Liu, Yuhua Qian, Jue Li +2
Bivariate causal direction identification is a fundamental and vital problem in the causal inference field. Among binary causal methods, most methods based on additive noise only u…