1 citations · 1 across the 3 of their papers we have counts for
4 papers
Routed Continual Learning
Michael Philip, Mahesh Balakrishnan, David Geraghty +3
Agents deployed at scale repeatedly encounter related problems, and it is natural to let them learn from each other's experience rather than starting over each time. Unfortunately,…
Sanity Checks for Agentic Data Science
Zachary T. Rewolinski, Austin V. Zane, Hao Huang +4
Agentic data science (ADS) pipelines have grown rapidly in both capability and adoption, with systems such as OpenAI Codex now able to directly analyze datasets and produce answers…
PCS Workflow for Veridical Data Science in the Age of AI
Zachary T. Rewolinski, Bin Yu
Data science is a pillar of artificial intelligence (AI), which is transforming nearly every domain of human activity, from the social and physical sciences to engineering and medi…
Local MDI+: Local Feature Importances for Tree-Based Models
Zhongyuan Liang, Zachary T. Rewolinski, Abhineet Agarwal +2
Tree-based ensembles such as random forests remain the go-to for tabular data over deep learning models due to their prediction performance and computational efficiency. These adva…