Matthew N. Bernstein

If you work in a quantitative or technical field, there is little doubt that you or your team has worked long and hard to define which metrics to measure and track.

Attention is a type of layer in a neural network that is widely regarded to be one of the most important breakthroughs that enabled the development of modern AI systems and large language models.

Euler’s number $e := 2.71828\dots$ has, to me, always been a semi-mysterious number.

If you’re a practitioner of machine learning, then there is little doubt you have seen or used an algorithm that falls into the general category of kernel methods.

The dot product is a fundamental operation on two Euclidean vectors that captures a notion of similarity between the vectors.

Cells are crowded spaces packed with biomolecules colliding and interacting with one another.

I am currently reading Sun Tzu’s Art of War and am finding much wisdom in it.

In Part 1 of this series, we introduced the denoising diffusion probabilistic model for modeling and sampling from complex distributions.

Diffusion models are a family of state-of-the-art probabilistic generative models that have achieved ground breaking results in a number of fields ranging from image generation to protein structure design.

We human beings use our vision as our chief sense for understanding the world, and thus when we are confronted with data, we try to understand that data through visualization.