Fait Poms

R2E2: low-latency path tracing of terabyte-scale scenes using thousands of cloud CPUs

Mandoline: Model Evaluation under Distribution Shift

Learning Rare Category Classifiers on a Tight Labeling Budget

Low-Shot Validation: Active Importance Sampling for Estimating Classifier Performance on Rare Categories

Background Splitting: Finding Rare Classes in a Sea of Background

Train and You'll Miss It: Interactive Model Iteration with Weak Supervision and Pre-Trained Embeddings