24 citations · 68 across the 7 of their papers we have counts for
8 papers
AIRIVA: A Deep Generative Model of Adaptive Immune Repertoires
Melanie F. Pradier, Niranjani Prasad, Paidamoyo Chapfuwa +8
Recent advances in immunomics have shown that T-cell receptor (TCR) signatures can accurately predict active or recent infection by leveraging the high specificity of TCR binding t…
Flexible Triggering Kernels for Hawkes Process Modeling
Yamac Alican Isik, Connor Davis, Paidamoyo Chapfuwa +1
Recently proposed encoder-decoder structures for modeling Hawkes processes use transformer-inspired architectures, which encode the history of events via embeddings and self-attent…
Capturing Actionable Dynamics with Structured Latent Ordinary Differential Equations
Paidamoyo Chapfuwa, Sherri Rose, Lawrence Carin +2
End-to-end learning of dynamical systems with black-box models, such as neural ordinary differential equations (ODEs), provides a flexible framework for learning dynamics from data…
Enabling Counterfactual Survival Analysis with Balanced Representations
Paidamoyo Chapfuwa, Serge Assaad, Shuxi Zeng +3
Balanced representation learning methods have been applied successfully to counterfactual inference from observational data. However, approaches that account for survival outcomes…
Survival Cluster Analysis
Paidamoyo Chapfuwa, Chunyuan Li, Nikhil Mehta +2
Conventional survival analysis approaches estimate risk scores or individualized time-to-event distributions conditioned on covariates. In practice, there is often great population…
Survival Function Matching for Calibrated Time-to-Event Predictions
Paidamoyo Chapfuwa, Chenyang Tao, Lawrence Carin +1
Models for predicting the time of a future event are crucial for risk assessment, across a diverse range of applications. Existing time-to-event (survival) models have focused prim…
NASH: Toward End-to-End Neural Architecture for Generative Semantic Hashing
Dinghan Shen, Qinliang Su, Paidamoyo Chapfuwa +4
Semantic hashing has become a powerful paradigm for fast similarity search in many information retrieval systems. While fairly successful, previous techniques generally require two…
Adversarial Time-to-Event Modeling
Paidamoyo Chapfuwa, Chenyang Tao, Chunyuan Li +4
Modern health data science applications leverage abundant molecular and electronic health data, providing opportunities for machine learning to build statistical models to support…