Projects, Products, Practice, and Pitfalls: A Hands-On Approach to Advanced Data Analytics Julia Lane, Rayid Ghani, Frauke Kreuter, Anna-Carolina Haensch, and Maryah Garner Projects, Products, Practice, and Pitfalls: A Hands-On Approach to Advanced Data Analytics ">Read more
Identifying housing-sensitive health conditions using machine learning O. Chakraborty, K. Dragan, I. Ellen, S. Glied, R. A. Howland, S. S. Wang, and D. B. Neill Identifying housing-sensitive health conditions using machine learning ">Read more
Efficient discovery of heterogeneous treatment effects in randomized experiments via anomalous pattern detection Edward McFowland III, Sriram Somanchi, and Daniel B. Neill Efficient discovery of heterogeneous treatment effects in randomized experiments via anomalous pattern detection ">Read more
Fairness and bias of machine learning approaches for diabetes screening in the Emergency Department Isaac Bohart, [...], Daniel B. Neill*, David Lee* Fairness and bias of machine learning approaches for diabetes screening in the Emergency Department ">Read more
Auditing predictive models for intersectional biases Kate Boxer, Edward McFowland III, and Daniel B. Neill Auditing predictive models for intersectional biases ">Read more
Insufficiently justified disparate impact: a new criterion for fair recommendations Neil Menghani, Edward McFowland III, and Daniel B. Neill Insufficiently justified disparate impact: a new criterion for fair recommendations ">Read more
Fairness and bias of machine learning in healthcare and medicine Isaac Bohart, Daniel B. Neill, and David Lee Fairness and bias of machine learning in healthcare and medicine ">Read more
PROVIDENT: development and validation of a machine learning model to predict neighborhood-level overdose risk in Rhode Island Bennett Allen, [...], Magdalena Cerda, Daniel B. Neill PROVIDENT: development and validation of a machine learning model to predict neighborhood-level overdose risk in Rhode Island ">Read more
Neighborhood-level risk factors for severe hyperglycemia among ED patients without a prior diabetes diagnosis Christian Koziatek, Isaac Bohart, [...], Daniel B. Neill, David Lee Neighborhood-level risk factors for severe hyperglycemia among ED patients without a prior diabetes diagnosis ">Read more
SPATE-GAN: Improved generative modeling of dynamic spatio-temporal patterns with an autoregressive embedding loss K. Klemmer, T. Xu, B. Acciaio, and D. B. Neill SPATE-GAN: Improved generative modeling of dynamic spatio-temporal patterns with an autoregressive embedding loss ">Read more
Positional encoder graph neural networks for geographic data Konstantin Klemmer, Nathan S. Safir, and D. B. Neill Positional encoder graph neural networks for geographic data ">Read more
Provable detection of propagating sampling bias in prediction models Pavan Ravishankar, Qingyu Mo, Edward McFowland III, and Daniel B. Neill Provable detection of propagating sampling bias in prediction models ">Read more