9 citations · 10 across the 7 of their papers we have counts for
4 papers · 1 filter
Beyond LoRA: Exploring Efficient Fine-Tuning Techniques for Time Series Foundational Models
Divij Gupta, Anubhav Bhatti, Surajsinh Parmar
Time Series Foundation Models (TSFMs) have recently garnered attention for their ability to model complex, large-scale time series data across domains such as retail, finance, and…
Interpretable Vital Sign Forecasting with Model Agnostic Attention Maps
Yuwei Liu, Chen Dan, Anubhav Bhatti +4
Sepsis is a leading cause of mortality in intensive care units (ICUs), representing a substantial medical challenge. The complexity of analyzing diverse vital signs to predict seps…
Low-Rank Adaptation of Time Series Foundational Models for Out-of-Domain Modality Forecasting
Divij Gupta, Anubhav Bhatti, Suraj Parmar +4
Low-Rank Adaptation (LoRA) is a widely used technique for fine-tuning large pre-trained or foundational models across different modalities and tasks. However, its application to ti…
Vital Sign Forecasting for Sepsis Patients in ICUs
Anubhav Bhatti, Yuwei Liu, Chen Dan +4
Sepsis and septic shock are a critical medical condition affecting millions globally, with a substantial mortality rate. This paper uses state-of-the-art deep learning (DL) archite…