4 citations · 6 across the 9 of their papers we have counts for
9 papers
SurvivalPFN: Amortizing Survival Prediction via In-Context Bayesian Inference
Shi-ang Qi, Vahid Balazadeh, Michael Cooper +2
Survival analysis provides a powerful statistical framework for modeling time-to-event outcomes in the presence of censoring. However, selecting an appropriate estimator from the m…
Position: Stop Chasing the C-index when Evaluating Survival Analysis Models
Christian Marius Lillelund, Shi-ang Qi, Russell Greiner +1
The current state of evaluation in survival analysis is plagued by the persistent use of evaluation metrics in ways that are misaligned with the stated modeling objective. In addit…
Overcoming Dependent Censoring in the Evaluation of Survival Models
Christian Marius Lillelund, Shi-ang Qi, Russell Greiner
Dependent censoring occurs when the event time and censoring time are not conditionally independent given the observed covariates. This complicates survival model evaluation becaus…
Toward Conditional Distribution Calibration in Survival Prediction
Shi-ang Qi, Yakun Yu, Russell Greiner
Survival prediction often involves estimating the time-to-event distribution from censored datasets. Previous approaches have focused on enhancing discrimination and marginal calib…
MENSA: A Multi-Event Network for Survival Analysis with Trajectory-based Likelihood Estimation
Christian Marius Lillelund, Ali Hossein Gharari Foomani, Weijie Sun +2
Most existing time-to-event methods focus on either single-event or competing-risks settings, leaving multi-event scenarios relatively underexplored. In many healthcare application…
Conformalized Survival Distributions: A Generic Post-Process to Increase Calibration
Shi-ang Qi, Yakun Yu, Russell Greiner
Discrimination and calibration represent two important properties of survival analysis, with the former assessing the model's ability to accurately rank subjects and the latter eva…
iHAS: Instance-wise Hierarchical Architecture Search for Deep Learning Recommendation Models
Yakun Yu, Shi-ang Qi, Jiuding Yang +2
Current recommender systems employ large-sized embedding tables with uniform dimensions for all features, leading to overfitting, high computational cost, and suboptimal generalizi…
ConKI: Contrastive Knowledge Injection for Multimodal Sentiment Analysis
Yakun Yu, Mingjun Zhao, Shi-ang Qi +6
Multimodal Sentiment Analysis leverages multimodal signals to detect the sentiment of a speaker. Previous approaches concentrate on performing multimodal fusion and representation…
An Effective Meaningful Way to Evaluate Survival Models
Shi-ang Qi, Neeraj Kumar, Mahtab Farrokh +5
One straightforward metric to evaluate a survival prediction model is based on the Mean Absolute Error (MAE) -- the average of the absolute difference between the time predicted by…