Physics and Python stuff. Most of the videos here are either adapted from class lectures or solving physics problems. I ...

The normal distribution is a continuous probability distribution that is symmetrical, bell-shaped, and centred around its mean. It is one of the most important distributions in statistics because many ...

Regression models with intractable normalizing constants are valuable tools for analyzing complex data structures, yet ...

Visually, the larger the variance, the "fatter" a probability distribution will be. In finance, if something like an investment has a greater variance, it may be interpreted as more risky or volatile.

end{align}\] The binomial distribution can be represented as a graph by plotting the number of successes \((x)\) against the probability of each outcome \(\Pr(X=x)\). The shape of the graph depends on ...

In this paper, we propose a Predicate Probability Distribution based Loss (PPDL) to train the biased SGG models and obtain unbi-ased Scene Graphs ultimately. Firstly, we propose a predi-cate ...

We propose a Quantum Probability Model to describe the partially observable target positions, and we use Upper Confidence Tree (UCT) algorithm to find out the best searching and tracking route based ...

Markov Affinity-based Graph Imputation of Cells (MAGIC) is an algorithm for denoising high-dimensional data most commonly applied to single-cell RNA sequencing data. MAGIC learns the manifold data, ...

With Netdata, you get real-time, per-second updates. Clear insights at a glance, no complexity. All heroes have a great origin story. Click to discover ours. In 2013, at the company where Costa ...