4 papers · 1 filter
Multi-Task Bayesian In-Context Learning
Qingyang Zhu, Eric Karl Oermann, Kyunghyun Cho
Bayesian predictive inference provides a principled framework for uncertainty quantification, data efficiency, and robust generalization. However, exact inference is often intracta…
Large Language Models Predict Functional Outcomes after Acute Ischemic Stroke
Anjali K. Kapoor, Anton Alyakin, Jin Vivian Lee +8
Accurate prediction of functional outcomes after acute ischemic stroke can inform clinical decision-making and resource allocation. Prior work on modified Rankin Scale (mRS) predic…
Large-Scale Multi-omic Biosequence Transformers for Modeling Protein-Nucleic Acid Interactions
Sully F. Chen, Robert J. Steele, Glen M. Hocky +3
The transformer architecture has revolutionized bioinformatics and driven progress in the understanding and prediction of the properties of biomolecules. To date, most biosequence…
Gateformer: Advancing Multivariate Time Series Forecasting through Temporal and Variate-Wise Attention with Gated Representations
Yu-Hsiang Lan, Eric K. Oermann
There has been a recent surge of interest in time series modeling using the Transformer architecture. However, forecasting multivariate time series with Transformer presents a uniq…