Discover how probability distribution methods can help predict stock market returns and improve investment decisions. Learn ...

Probability theory is indispensable in computer science: It is at the core of artificial intelligence and machine learning, which require decision making under uncertainty. It is integral to CS theory ...

Autoregressive visual generation models have emerged as a groundbreaking approach to image synthesis, drawing inspiration from language model token prediction mechanisms. These innovative models ...

Conformist and anticonformist biases in acquiring cultural variants have been documented in humans and several nonhuman species. We introduce a framework for quantifying these biases when cultural ...

Probability distribution is an essential concept in statistics, helping us understand the likelihood of different outcomes in a random experiment. Whether you’re a student, researcher, or professional ...

Quantum annealing (QA) can be competitive to classical algorithms in optimizing continuous-variable functions when running on appropriate hardware, show researchers from Tokyo Tech. By comparing the ...

Cumulative probability is an essential concept in the world of statistics and probability theory. It refers to the likelihood that a random variable will take a value equal to or less than a specific ...

I am new to using SALib and currently, I have a model that contains continuous and discrete input variables. I read the closed issues and understood the workaround of rounding the floats to integers ...