(Include but not limited to)
Track 1: Statistical Computing and Statistical Learning Methods
Statistical Computing Theory and Algorithm Design
Bayesian Statistical Computing and Inference Methods
Monte Carlo Methods and Markov Chain Monte Carlo (MCMC)
High-Dimensional Statistical Computing and Dimension Reduction Methods
Regularization and Sparse Modeling in Statistical Learning
Nonparametric and Semi-parametric Statistical Methods
Time Series Statistical Modeling and Prediction
Spatial Statistics and Spatio-temporal Data Analysis
Causal Inference and Statistical Decision Theory
Statistical Model Selection and Model Averaging
Robust Statistics and Anomaly Detection Methods
Numerical Optimization Methods in Statistical Computing
Statistical Software and Reproducible Computing
Application of Statistical Computing in Big Data
Uncertainty Quantification in Statistical Inference
Track 2: Machine Learning and Intelligent Algorithms
Supervised Learning, Unsupervised Learning and Semi-supervised Learning
Deep Learning and Neural Network Algorithms
Reinforcement Learning and Sequential Decision Making
Transfer Learning, Meta-Learning and Small Sample Learning
Ensemble Learning and Model Fusion Methods
Graph Neural Networks and Graph Representation Learning
Generative Models and Probabilistic Modeling
Kernel Methods and Support Vector Machines
Clustering Analysis and Dimension Reduction Algorithms
Online Learning and Incremental Learning
Federated Learning and Distributed Machine Learning
Interpretable Machine Learning and Model Transparency
Optimization Theory in Machine Learning
AutoML and Neural Architecture Search
Application of Machine Learning in Scientific Discovery
Track 3: Simulation Modeling and Intelligent System Applications
Discrete Event Simulation and Continuous System Simulation
Monte Carlo Simulation and Random Simulation
Agent-Based Modeling and Simulation
Multi-physical Field Coupling Simulation and Multi-scale Modeling
Digital Twin and Virtual Simulation System
Simulation Optimization and Proxy Model Methods
High-Performance Computing and Parallel Simulation
Simulation Model Validation, Calibration and Confirmation (VV&A)
Uncertainty Quantification and Sensitivity Analysis
Machine Learning-Driven Simulation Acceleration
Physical Information Neural Networks and Hybrid Modeling
Complex System Modeling and Simulation
Social, Economic and Ecosystem Simulation
Application of Simulation in Industries, Healthcare, Transportation and Other Fields
......