Z-Transforms and its Inference on Partially Observable Point Processes. - Young Lee; Thanh Vinh Vo; Kar Wai Lim; Harold Soh (IJCAI, 2018)

Generation meets recommendation: proposing novel items for groups of users. - Thanh Vinh Vo; Harold Soh (RecSys, 2018)

A Causal Modeling Framework with Stochastic Confounders. - Thanh Vinh Vo; Pengfei Wei; Wicher Bergsma; Tze-Yun Leong (CoRR, 2020)

Causal Modeling with Stochastic Confounders. - Thanh Vinh Vo; Pengfei Wei 001; Wicher Bergsma; Tze-Yun Leong (AISTATS, 2021)

Adaptive Multi-Source Causal Inference. - Thanh Vinh Vo; Pengfei Wei; Trong Nghia Hoang; Tze-Yun Leong (CoRR, 2021)

Federated Estimation of Causal Effects from Observational Data. - Thanh Vinh Vo; Trong Nghia Hoang; Young Lee; Tze-Yun Leong (CoRR, 2021)

Adaptive Multi-Source Causal Inference from Observational Data. - Thanh Vinh Vo; Pengfei Wei 001; Trong Nghia Hoang; Tze-Yun Leong (CIKM, 2022)

An Adaptive Kernel Approach to Federated Learning of Heterogeneous Causal Effects. - Thanh Vinh Vo; Arnab Bhattacharyya 001; Young Lee; Tze-Yun Leong (NeurIPS, 2022)

Bayesian federated estimation of causal effects from observational data. - Thanh Vinh Vo; Young Lee; Trong Nghia Hoang; Tze-Yun Leong (UAI, 2022)

Hierarchical Reinforcement Learning with Human-AI Collaborative Sub-Goals Optimization. - Haozhe Ma; Thanh Vinh Vo; Tze-Yun Leong (AAMAS, 2023)

Discovering Low-Dimensional Causal Pathways between Multiple Interacting Neuronal Populations. - Evangelos Sigalas; Thanh Vinh Vo; Tze-Yun Leong; Camilo Libedinsky (CogSci, 2023)

Federated Learning of Causal Effects from Incomplete Observational Data. - Thanh Vinh Vo; Young Lee; Tze-Yun Leong (CoRR, 2023)

Transfer Kernel Learning for Multi-Source Transfer Gaussian Process Regression. - Pengfei Wei 001; Thanh Vinh Vo; Xinghua Qu; Yew Soon Ong; Zejun Ma (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

Mixed-Initiative Bayesian Sub-Goal Optimization in Hierarchical Reinforcement Learning. - Haozhe Ma; Thanh Vinh Vo; Tze-Yun Leong (AAMAS, 2024)

Decoupled Prompt-Adapter Tuning for Continual Activity Recognition. - Di Fu; Thanh Vinh Vo; Haozhe Ma; Tze-Yun Leong (CoLLAs, 2024)

Reward Shaping for Reinforcement Learning with An Assistant Reward Agent. - Haozhe Ma; Kuankuan Sima; Thanh Vinh Vo; Di Fu; Tze-Yun Leong (ICML, 2024)

Knowledge Sharing and Transfer via Centralized Reward Agent for Multi-Task Reinforcement Learning. - Haozhe Ma; Zhengding Luo; Thanh Vinh Vo; Kuankuan Sima; Tze-Yun Leong (CoRR, 2024)

Highly Efficient Self-Adaptive Reward Shaping for Reinforcement Learning. - Haozhe Ma; Zhengding Luo; Thanh Vinh Vo; Kuankuan Sima; Tze-Yun Leong (ICLR, 2025)

Causal Policy Learning in Reinforcement Learning: Backdoor-Adjusted Soft Actor-Critic. - Thanh Vinh Vo; Young Lee; Haozhe Ma; Chien Lu; Tze-Yun Leong (CoRR, 2025)

Federated causal inference from observational data. - Thanh Vinh Vo; Young Lee; Tze-Yun Leong (Mach. Learn., 2025)