1 citations · 1 across the 7 of their papers we have counts for
8 papers
SL-S4Wave: Self-Supervised Learning of Physiological Waveforms with Structured State Space Models
Feng Wu, Harsh Deep, Eric Lehman +5
Modeling long-sequence medical time series data, such as electrocardiograms (ECG), poses significant challenges due to high sampling rates, multichannel signal complexity, inherent…
Can we generate portable representations for clinical time series data using LLMs?
Zongliang Ji, Yifei Sun, Andre Amaral +2
Deploying clinical ML is slow and brittle: models that work at one hospital often degrade under distribution shifts at the next. In this work, we study a simple question -- can lar…
DynaSubVAE: Adaptive Subgrouping for Scalable and Robust OOD Detection
Tina Behrouzi, Sana Tonekaboni, Rahul G. Krishnan +1
Real-world observational data often contain existing or emerging heterogeneous subpopulations that deviate from global patterns. The majority of models tend to overlook these under…
Beyond Masked and Unmasked: Discrete Diffusion Models via Partial Masking
Chen-Hao Chao, Wei-Fang Sun, Hanwen Liang +2
Masked diffusion models (MDM) are powerful generative models for discrete data that generate samples by progressively unmasking tokens in a sequence. Each token can take one of two…
ExOSITO: Explainable Off-Policy Learning with Side Information for Intensive Care Unit Blood Test Orders
Zongliang Ji, Andre Carlos Kajdacsy-Balla Amaral, Anna Goldenberg +1
Ordering a minimal subset of lab tests for patients in the intensive care unit (ICU) can be challenging. Care teams must balance between ensuring the availability of the right info…
Learning Predictive Checklists with Probabilistic Logic Programming
Yukti Makhija, Edward De Brouwer, Rahul G. Krishnan
Checklists have been widely recognized as effective tools for completing complex tasks in a systematic manner. Although originally intended for use in procedural tasks, their inter…
Measurement Scheduling for ICU Patients with Offline Reinforcement Learning
Zongliang Ji, Anna Goldenberg, Rahul G. Krishnan
Scheduling laboratory tests for ICU patients presents a significant challenge. Studies show that 20-40% of lab tests ordered in the ICU are redundant and could be eliminated withou…
MultiResFormer: Transformer with Adaptive Multi-Resolution Modeling for General Time Series Forecasting
Linfeng Du, Ji Xin, Alex Labach +3
Transformer-based models have greatly pushed the boundaries of time series forecasting recently. Existing methods typically encode time series data into using on…