63 citations · 63 across the 2 of their papers we have counts for
3 papers
cs.AI2026
Energy Ring: Stabilizing Feature Energy for Reliable Test-Time Discovery
Tianle Liu, Fan Lyu, Tingliang Feng +6
Test-Time Discovery (TTD) aims to recognize known classes and detect novel ones while the model is already deployed, operating directly on a continual unlabeled test-time stream. E…
stat.ME2026
Bayesian Propensity Score-Augmented Latent Factor Models for Causal Inference with Time-Series Cross-Sectional Data
Licheng Liu
We propose a Bayesian propensity score-augmented latent factor model for causal inference with time-series cross-sectional data. The framework explicitly models the treatment assig…
stat.ME2021★ 63 cited
A Practical Guide to Counterfactual Estimators for Causal Inference with Time-Series Cross-Sectional Data
Licheng Liu, Ye Wang, Yiqing Xu
This paper introduces a simple framework of counterfactual estimation for causal inference with time-series cross-sectional data, in which we estimate the average treatment effect…