Research
Data-driven Discovery of Wildfire Spread Models
Bryan Quaife and Jhamieka Greenwood detail their wSINDy model that can be trained on experimental data and reveal fire spread mechanisms.
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Conor Rowan provides a history of equation discovery and symbolic regression and discusses how AI may impact future mathematical breakthroughs.
Node degree volatility, which quantifies the rate of change in a node’s functional connectivity, helps identify seizure onset zones.
Arthur Montanari, Ana Elisa Barioni, and Adilson Motter discuss the mathematics of collective group dynamics in animals and potential applications.
Matthew Francis details a new paper that explores the physics behind why these smoke vortices defied ordinary atmospheric dynamics.
Gabriela Kováčová and Igor Cialenco detail time-inconsistent problems under model uncertainty through multi-objective stochastic control.
Dhyey Mavani overviews a new open-source Python package that uses chip-firing to analyze complex, cascading network dynamics.
Ernest Davis reviews Seeing Foucault’s Pendulum: Between Science, Politics, and Art. By Michael Hagner, translated by Robert Savage.
Mark Levi debunks the claim that binoculars with large objective lenses make objects appear brighter, thus making it easier to see in low light.
Kivmars Bowling recounts the recent publishing workshop for early-career researchers jointly hosted by ICMSEC-CAS and SIAM in Beijing.
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