35 citations · 52 across the 10 of their papers we have counts for
6 papers · 1 filter
Scaling Recurrence-aware Foundation Models for Clinical Records via Next-Visit Prediction
Haresh Rengaraj Rajamohan, Xiang Gao, Weicheng Zhu +10
While large-scale pretraining has revolutionized language modeling, its potential remains underexplored in healthcare with structured electronic health records (EHRs). We present R…
Foundation Models for Clinical Records at Health System Scale
Haresh Rengaraj Rajamohan, Xiang Gao, Weicheng Zhu +5
Large-scale pretraining has transformed modeling of language and other data types, but its potential remains underexplored in healthcare with structured electronic health records (…
A Monte Carlo Framework for Calibrated Uncertainty Estimation in Sequence Prediction
Qidong Yang, Weicheng Zhu, Joseph Keslin +3
Probabilistic prediction of sequences from images and other high-dimensional data is a key challenge, particularly in risk-sensitive applications. In these settings, it is often de…
Making Self-supervised Learning Robust to Spurious Correlation via Learning-speed Aware Sampling
Weicheng Zhu, Sheng Liu, Carlos Fernandez-Granda +1
Self-supervised learning (SSL) has emerged as a powerful technique for learning rich representations from unlabeled data. The data representations are able to capture many underlyi…
Deep Probability Estimation
Sheng Liu, Aakash Kaku, Weicheng Zhu +8
Reliable probability estimation is of crucial importance in many real-world applications where there is inherent (aleatoric) uncertainty. Probability-estimation models are trained…
Variationally Regularized Graph-based Representation Learning for Electronic Health Records
Weicheng Zhu, Narges Razavian
Electronic Health Records (EHR) are high-dimensional data with implicit connections among thousands of medical concepts. These connections, for instance, the co-occurrence of disea…