The general problem of determining causal dependencies in an unknown time-evolving system from time series observations is of great interest in many fields. Examples include inferring neuronal ...

A research team has developed a novel method for estimating the predictability of complex dynamical systems. Their work, "Time-lagged recurrence: A data-driven method to estimate the predictability of ...

Last Thursday, Meta announced the newest iteration of its large language model (LLM), Llama 3. The newest model will aim to dislodge OpenAI as the market leader through various improvements driven by ...

Scientists usually use a hypergraph model to predict dynamic behaviors. But the opposite problem is interesting, too. What if researchers can observe the dynamics but don't have access to a reliable ...

Ragnar van der Merwe received funding from the John Templeton Foundation as part of the project The Evolution of Complexity hosted at Bath University. Alex Broadbent received funding from the John ...

Demonstrating the applicability of αη across a diverse range of systems. These include a canonical dynamical system (Rössler attractor), simulation data for slow earthquakes (spring-slider system), a ...

Juniper Lovato, Director of Outreach for Complex Systems, University of VermontLimits of individual consent and models of distributed consent in online social networksPersonal data is not discrete in ...