From the 1 of 7 linked papers with an AI index.
7 papers
ResidencyRL: Reinforcement Learning in Simulated Clinical Environments
Valentin Liévin, Samuel Schmidgall, Tim Strother +32
In medical education, physicians convert academic knowledge into clinical expertise through residency: years of training across thousands of encounters, with diverse sources of fee…
Causal Foundation Models with Continuous Treatments
Christopher Stith, Medha Barath, Vahid Balazadeh +2
The paper introduces a causal foundation model that can predict individual treatment-response curves for continuous interventions, using a transformer trained on a synthetic causal…
Frequentist Consistency of Prior-Data Fitted Networks for Causal Inference
Valentyn Melnychuk, Vahid Balazadeh, Stefan Feuerriegel +1
Foundation models based on prior-data fitted networks (PFNs) have shown strong empirical performance in causal inference by framing the task as an in-context learning problem. Howe…
SurvivalPFN: Amortizing Survival Prediction via In-Context Bayesian Inference
Shi-ang Qi, Vahid Balazadeh, Michael Cooper +2
Survival analysis provides a powerful statistical framework for modeling time-to-event outcomes in the presence of censoring. However, selecting an appropriate estimator from the m…
Physics Context Builders: A Modular Framework for Physical Reasoning in Vision-Language Models
Vahid Balazadeh, Mohammadmehdi Ataei, Hyunmin Cheong +2
Physical reasoning remains a significant challenge for Vision-Language Models (VLMs). This limitation arises from an inability to translate learned knowledge into predictions about…
CausalPFN: Amortized Causal Effect Estimation via In-Context Learning
Vahid Balazadeh, Hamidreza Kamkari, Valentin Thomas +4
Causal effect estimation from observational data is fundamental across various applications. However, selecting an appropriate estimator from dozens of specialized methods demands…