10 citations · 16 across the 5 of their papers we have counts for
7 papers
When Repeated Measurements Hurt Tabular Foundation Models
Yixiang Liu, Ruizhe Deng, Bibhas Chakraborty +2
Tabular foundation models (TFMs) achieve state-of-the-art performance on IID benchmarks, but how do they respond to repeated measurements at the same inputs? Across six TFMs, synth…
PFN-TS: Thompson Sampling for Contextual Bandits via Prior-Data Fitted Networks
Yan Shuo Tan, Kenyon Ng, Ruizhe Deng +3
Thompson sampling is a widely used strategy for contextual bandits: at each round, it samples a reward function from a Bayesian posterior and acts greedily under that sample. Prior…
Bayesian Machine Learning for Estimating Optimal Dynamic Treatment Regimes with Ordinal Outcomes
Xinru Wang, Tanujit Chakraborty, Bibhas Chakraborty
Dynamic treatment regimes (DTRs) are sequences of decision rules designed to tailor treatment based on patients' treatment history and evolving disease status. Ordinal outcomes fre…
Artificial Intelligence-based Decision Support Systems for Precision and Digital Health
Nina Deliu, Bibhas Chakraborty
Precision health, increasingly supported by digital technologies, is a domain of research that broadens the paradigm of precision medicine, advancing everyday healthcare. This visi…
Skew-Probabilistic Neural Networks for Learning from Imbalanced Data
Shraddha M. Naik, Tanujit Chakraborty, Madhurima Panja +2
Real-world datasets often exhibit imbalanced data distribution, where certain class levels are severely underrepresented. In such cases, traditional pattern classifiers have shown…
Thompson sampling for zero-inflated count outcomes with an application to the Drink Less mobile health study
Xueqing Liu, Nina Deliu, Tanujit Chakraborty +2
Mobile health (mHealth) interventions often aim to improve distal outcomes, such as clinical conditions, by optimizing proximal outcomes through just-in-time adaptive interventions…
Incorporating nonparametric methods for estimating causal excursion effects in mobile health with zero-inflated count outcomes
Xueqing Liu, Tianchen Qian, Lauren Bell +1
In mobile health, tailoring interventions for real-time delivery is of paramount importance. Micro-randomized trials have emerged as the "gold-standard" methodology for developing…