2 citations · 7 across the 17 of their papers we have counts for
6 papers · 1 filter
ECG-Byte: A Tokenizer for End-to-End Generative Electrocardiogram Language Modeling
William Han, Chaojing Duan, Michael A. Rosenberg +2
Large Language Models (LLMs) have demonstrated exceptional versatility across domains, including applications to electrocardiograms (ECGs). A growing body of work focuses on genera…
Dynamics as Prompts: In-Context Learning for Sim-to-Real System Identifications
Xilun Zhang, Shiqi Liu, Peide Huang +4
Sim-to-real transfer remains a significant challenge in robotics due to the discrepancies between simulated and real-world dynamics. Traditional methods like Domain Randomization o…
Evaluating Durability: Benchmark Insights into Multimodal Watermarking
Jielin Qiu, William Han, Xuandong Zhao +3
With the development of large models, watermarks are increasingly employed to assert copyright, verify authenticity, or monitor content distribution. As applications become more mu…
Recent Advances, Applications, and Open Challenges in Machine Learning for Health: Reflections from Research Roundtables at ML4H 2023 Symposium
Hyewon Jeong, Sarah Jabbour, Yuzhe Yang +40
The third ML4H symposium was held in person on December 10, 2023, in New Orleans, Louisiana, USA. The symposium included research roundtable sessions to foster discussions between…
Entity6K: A Large Open-Domain Evaluation Dataset for Real-World Entity Recognition
Jielin Qiu, William Han, Winfred Wang +6
Open-domain real-world entity recognition is essential yet challenging, involving identifying various entities in diverse environments. The lack of a suitable evaluation dataset ha…
Interpretation of Intracardiac Electrograms Through Textual Representations
William Jongwon Han, Diana Gomez, Avi Alok +5
Understanding the irregular electrical activity of atrial fibrillation (AFib) has been a key challenge in electrocardiography. For serious cases of AFib, catheter ablations are per…