3 citations · 3 across the 4 of their papers we have counts for
6 papers
MolLedger: An Additive Graph Neural Network with Chemically Grounded ADME Attributions
Christina X. Ji
Optimizing absorption, distribution, metabolism, and excretion (ADME) is an important part of small molecule drug discovery. Many machine learning models have been built to predict…
Pearl: A Foundation Model for Placing Every Atom in the Right Location
Genesis Research Team, Alejandro Dobles, Nina Jovic +37
Accurately predicting the three-dimensional structures of protein-ligand complexes remains a fundamental challenge in computational drug discovery that limits the pace and success…
Seq-to-Final: A Benchmark for Tuning from Sequential Distributions to a Final Time Point
Christina X Ji, Ahmed M Alaa, David Sontag
Distribution shift over time occurs in many settings. Leveraging historical data is necessary to learn a model for the last time point when limited data is available in the final p…
Large-Scale Study of Temporal Shift in Health Insurance Claims
Christina X Ji, Ahmed M Alaa, David Sontag
Most machine learning models for predicting clinical outcomes are developed using historical data. Yet, even if these models are deployed in the near future, dataset shift over tim…
Finding Regions of Heterogeneity in Decision-Making via Expected Conditional Covariance
Justin Lim, Christina X Ji, Michael Oberst +3
Individuals often make different decisions when faced with the same context, due to personal preferences and background. For instance, judges may vary in their leniency towards cer…
Trajectory Inspection: A Method for Iterative Clinician-Driven Design of Reinforcement Learning Studies
Christina X. Ji, Michael Oberst, Sanjat Kanjilal +1
Reinforcement learning (RL) has the potential to significantly improve clinical decision making. However, treatment policies learned via RL from observational data are sensitive to…