Can Machine Learning Predict Chaos? This Paper from UT Austin Performs a Large-Scale Comparison of Modern Forecasting Methods on a Giant Dataset of 135 Chaotic Systems

The science of predicting chaotic systems lies at the intriguing intersection of physics and computer science. This field delves into understanding and forecasting the unpredictable nature of systems where small initial changes can lead to significantly divergent outcomes. It’s a realm where the butterfly effect reigns supreme, challenging the traditional notions of predictability and order. […]

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