283 citations · 516 across the 5 of their papers we have counts for
6 papers
MoCHA: Denoising Caption Supervision for Motion-Text Retrieval
Nikolai Warner, Cameron Ethan Taylor, Irfan Essa +1
Text-motion retrieval systems learn shared embedding spaces from motion-caption pairs via contrastive objectives. However, each caption is not a deterministic label but a sample fr…
AugLift: Depth-Aware Input Reparameterization Improves Domain Generalization in 2D-to-3D Pose Lifting
Nikolai Warner, Wenjin Zhang, Hamid Badiozamani +2
Lifting-based 3D human pose estimation infers 3D joints from 2D keypoints but generalizes poorly because coordinates alone are an ill-posed, sparse representation that disc…
A Set-Sequence Model for Time Series
Elliot L. Epstein, Apaar Sadhwani, Kay Giesecke
Many prediction problems across science and engineering, especially in finance and economics, involve large cross-sections of individual time series, where each unit (e.g., a loan,…
Interpretable Survival Prediction for Colorectal Cancer using Deep Learning
Ellery Wulczyn, David F. Steiner, Melissa Moran +20
Deriving interpretable prognostic features from deep-learning-based prognostic histopathology models remains a challenge. In this study, we developed a deep learning system (DLS) f…
Deep learning-based survival prediction for multiple cancer types using histopathology images
Ellery Wulczyn, David F. Steiner, Zhaoyang Xu +7
Prognostic information at diagnosis has important implications for cancer treatment and monitoring. Although cancer staging, histopathological assessment, molecular features, and c…
Deep Learning for Mortgage Risk
Justin Sirignano, Apaar Sadhwani, Kay Giesecke
We develop a deep learning model of multi-period mortgage risk and use it to analyze an unprecedented dataset of origination and monthly performance records for over 120 million mo…