Probabilistic Models

Probabilistic models are mathematical frameworks used to represent and analyze complex systems that involve uncertainty and randomness, enabling researchers to make predictions and informed decisions. By applying probabilistic models, researchers in various fields, including artificial intelligence, machine learning, and data science, can better understand and model real-world phenomena, such as pattern recognition, decision-making under uncertainty, and predictive analytics, ultimately driving advancements in areas like computer vision, natural language processing, and risk analysis.