Kiattikun Chobtham

According to our database, Kiattikun Chobtham authored at least 12 papers between 2008 and 2026.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2026

Reinforcement Learning to Discover a NorthEast Monsoon Index for Monthly Rainfall Prediction in Thailand.

Kiattikun Chobtham

CoRR, January, 2026

HydroGen: Hydrological Report Generation With Two-Stage Instruction-Tuned Multimodal Models, Temporal Prompts, and Knowledge-Guided Agents.

Pasith Thanapatpisarn, Kiattikun Chobtham, Kanoksri Sarinnapakorn, Peerapon Vateekul

IEEE Access, 2026

2025

Leveraging Teleconnections with Physics-Informed Graph Attention Networks for Long-Range Extreme Rainfall Forecasting in Thailand.

Kiattikun Chobtham, Kanoksri Sarinnapakorn, Kritanai Torsri, Prattana Deeprasertkul, Jirawan Kamma

CoRR, October, 2025

2024

Tuning structure learning algorithms with out-of-sample and resampling strategies.

Kiattikun Chobtham, Anthony C. Constantinou

Knowl. Inf. Syst., August, 2024

2023

Open problems in causal structure learning: A case study of COVID-19 in the UK.

Anthony C. Constantinou, Neville Kenneth Kitson, Yang Liu, Kiattikun Chobtham, Arian Hashemzadeh, Praharsh A. Nanavati, Rendani Mbuvha, Bruno Petrungaro

Expert Syst. Appl., December, 2023

Hybrid Bayesian network discovery with latent variables by scoring multiple interventions.

Kiattikun Chobtham, Anthony C. Constantinou, Neville Kenneth Kitson

Data Min. Knowl. Discov., 2023

A survey of Bayesian Network structure learning.

Neville Kenneth Kitson, Anthony C. Constantinou, Zhigao Guo, Yang Liu, Kiattikun Chobtham

Artif. Intell. Rev., 2023

2022

Effective and efficient structure learning with pruning and model averaging strategies.

Anthony C. Constantinou, Yang Liu, Neville Kenneth Kitson, Kiattikun Chobtham, Zhigao Guo

Int. J. Approx. Reason., 2022

Discovery and density estimation of latent confounders in Bayesian networks with evidence lower bound.

Kiattikun Chobtham, Anthony C. Constantinou

Proceedings of the International Conference on Probabilistic Graphical Models, 2022

2021

Large-scale empirical validation of Bayesian Network structure learning algorithms with noisy data.

Anthony C. Constantinou, Yang Liu, Kiattikun Chobtham, Zhigao Guo, Neville Kenneth Kitson

Int. J. Approx. Reason., 2021

2020

Bayesian network structure learning with causal effects in the presence of latent variables.

Kiattikun Chobtham, Anthony C. Constantinou

Proceedings of the International Conference on Probabilistic Graphical Models, 2020

2008

Formalization of Link Farm Structure Using Graph Grammar.

Kiattikun Chobtham, Athasit Surarerks, Arnon Rungsawang

Proceedings of the 22nd International Conference on Advanced Information Networking and Applications, 2008