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Vincent Guan

2 accepted papers

2026

A Call to Lagrangian Action: Learning Population Mechanics from Temporal Snapshots

ICML 2026spotlight

The population dynamics of molecules, cells, and organisms are governed by a number of unknown internal and external forces. In the last decade, population dynamics have predominately been modeled with Wasserstein gradient flows. However, since gradient flows minimize free energy, they fail to captu…

Cited by 0SourceScholar
2023

Ultra-marginal Feature Importance: Learning from Data with Causal Guarantees

AISTATS 2023poster

Scientists frequently prioritize learning from data rather than training the best possible model; however, research in machine learning often prioritizes the latter. Marginal contribution feature importance (MCI) was developed to break this trend by providing a useful framework for quantifying the r…