Articles tagged with Markov Processes
Scientists identify previously unrecognized mathematical property explaining why widely used evolutionary statistical models can produce convincing but incorrect conclusions. A new decomposition of Markov models revealed hidden symmetries, allowing researchers to answer long-standing questions about species diversity.
The Trace Institute aims to develop a unified mathematical theory of conscious observers and traces, potentially transforming our understanding of physics, neuroscience, and spirituality. With AI-assisted models, the institute seeks solutions to long-standing problems in these fields, innovating new technologies for society.
Scientists at National University of Singapore developed a hybrid generative machine learning model to explore structural disorders in complex materials. The model unveiled pathways to material disorder, shedding light on factors affecting piezoelectric response. It also found evidence that domain boundaries maximize entropy.
A new research paper challenges the idea that unlimited trials are needed to learn safe actions in unfamiliar environments. The team presents a fresh approach that ensures learning safe actions with complete confidence while managing tradeoffs between optimality and exposure to unsafe events.
Researchers from North Carolina State University identified a fundamental flaw in a commonly used pandemic model that causes it to severely underestimate disease spread. By modifying parts of an existing model, they substantially improved its accuracy when compared to real-world data on the COVID-19 Omicron variant.
A new AI tool helps governments decide whether to bail out a bank by predicting if the intervention will save money for taxpayers. The algorithm assesses financial implications and suggests optimal bailout strategies.
RUDN University mathematicians developed a model to optimize data center efficiency using Markov chains. Their method reduces server overheating and improves server capacity utilization, resulting in significant cost savings.
Researchers at the Santa Fe Institute and MIT find that continuous-time systems must have hidden states and finite hidden timesteps to exhibit two-time dynamics. This discovery has implications for understanding biomolecular processes, ecosystem evolution, and financial market behavior.
Researchers develop Markov model to provide personalized information for women undergoing infertility treatment, considering factors like age, body weight, and AMH blood levels. The model can be updated in real-time and translated into a physician-friendly app.
A new mathematical theorem developed by Carnegie Mellon University and University of Pittsburgh mathematicians proves that Pennsylvania's congressional district maps are likely the result of gerrymandering. The researchers used a Markov chain to analyze the characteristics of the current map, comparing it to randomly generated typical ...
MIT researchers have created an algorithm that enables a drone to monitor its health in real-time, allowing it to take proactive measures during delivery missions. The approach simplifies planning by separating vehicle-level and mission-level tasks, resulting in more efficient and reliable deliveries.
A recent study published in Proceedings of the Royal Society B analyzed the vocal sequences of seven different species and found that they appear to be generated by complex statistical processes more akin to human language. The findings suggest an intermediate step on the evolutionary path between animal communication and human language.