3 citations · 6 across the 5 of their papers we have counts for
6 papers
Bolzano: From Expert-Guided Proof Search to Automated Open-Problem Solving
Adrián Zámečník, Matěj Kripner, Martin Koutecký +5
Large language models are increasingly contributing to mathematical research, where progress often depends on efficient proof search, incremental improvements and careful verificat…
Probabilistic Seasonal Streamflow Forecasting Across California's Sierra Nevada Watersheds with Agentic AI
Ignacio Lopez-Gomez, Michael P. Brenner, Tapio Schneider
Accurate seasonal runoff forecasts are critical for managing California's reservoirs and water supply for millions of its residents. Winter snow accumulation provides a strong sour…
AIMIP Phase 1: systematic evaluations of AI weather and climate models
Brian Henn, Christopher S. Bretherton, Nikolay Koldunov +18
We present the AI weather and climate model intercomparison project (AIMIP), phase 1. Drawing from the rich tradition of intercomparisons in climate model development, we specify a…
Regional climate risk assessment from climate models using probabilistic machine learning
Zhong Yi Wan, Ignacio Lopez-Gomez, Robert Carver +4
Effective climate risk assessment is hindered by the resolution gap between coarse global climate models and the fine-scale information needed for regional decisions. We introduce…
Dynamical-generative downscaling of climate model ensembles
Ignacio Lopez-Gomez, Zhong Yi Wan, Leonardo Zepeda-Núñez +3
Regional high-resolution climate projections are crucial for many applications, such as agriculture, hydrology, and natural hazard risk assessment. Dynamical downscaling, the state…
A probabilistic framework for learning non-intrusive corrections to long-time climate simulations from short-time training data
Benedikt Barthel Sorensen, Leonardo Zepeda-Núñez, Ignacio Lopez-Gomez +4
Chaotic systems, such as turbulent flows, are ubiquitous in science and engineering. However, their study remains a challenge due to the large range scales, and the strong interact…