Here we are now at the middle of the fourth large part of this talk.get nowheremore quotes
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music + math
WELCOME TO THE 5TH DIMENSION | This isn't meant to be understood — it's meant to be enjoyed.
Love music and science? Explore my collaboration with Max Cooper where we tell the story of infinities and animate the digits of π. Both tracks appear on Max's Yearning for the Infinite album.
Another collaboration with Max!

# Max Cooper's Ascent — Making of the Music video

## Enter the 5th dimension

Ascent answers the question: if you were living in a 5-dimensional room and projected digits of $\pi$ onto its walls, what would you see?

## 1 · How it started — prototype scenes

Here, I show some early prototype scenes generated from the animation system during development and testing. There was a lot testing.

These scenes are short and evolve slowly. They built from keyframes (but fewer) in the same way as the final Ascent video.

The animations here have no audio.

## 2 · From one to many dimensions

A cube evolves from 2 to 8 dimensions. The colored lines in the center show the unit axes. This scene served as the inspiration for the start of the Ascent video. The scene ends with the dimensions shrinking back to zero, one at a time. Notice the variety in the complexity of the projected scene as we rotate through various angles.

MAX COOPER'S ASCENT PROTOTYPES | growth of dimensions (9:35)

## 3 · Attack of the toothpicks

One of my favourite scenes. Cubes are added to the scene as the camera zooms in. The lines are formed by the area maps of digits of $\pi$ projected onto faces of the cubes. Each scene evolves with one additional dimension added.

MAX COOPER'S ASCENT PROTOTYPES | lines (2:07)

## 4 · Plenty of corners for punishment

MAX COOPER'S ASCENT PROTOTYPES | corners (2:00)

## 5 · Mixed bag

A variety of short scenes in black-and-white and color. Rectangles correspond to area maps on the faces of the cube, color-coded by digit.

MAX COOPER'S ASCENT PROTOTYPES | mix (1:27)

## 6 · Snowstorm

Area maps projected onto cubes with transparency encoding the z-position (distance from camera).

MAX COOPER'S ASCENT PROTOTYPES | snowstorm (2:00)

## 7 · 2-hour color chill

A long and slow mix of various color scenes

MAX COOPER'S ASCENT PROTOTYPES | 2-hour color remix (2:03:19)

## 8 · 1-hour monochrome chill

A long and slow mix of various black-and-white scenes.

MAX COOPER'S ASCENT PROTOTYPES | 1-hour black-and-white remix (1:00:02)
news + thoughts

# Convolutional neural networks

Thu 17-08-2023

Nature uses only the longest threads to weave her patterns, so that each small piece of her fabric reveals the organization of the entire tapestry. – Richard Feynman

Following up on our Neural network primer column, this month we explore a different kind of network architecture: a convolutional network.

The convolutional network replaces the hidden layer of a fully connected network (FCN) with one or more filters (a kind of neuron that looks at the input within a narrow window).

Nature Methods Points of Significance column: Convolutional neural networks. (read)

Even through convolutional networks have far fewer neurons that an FCN, they can perform substantially better for certain kinds of problems, such as sequence motif detection.

Derry, A., Krzywinski, M & Altman, N. (2023) Points of significance: Convolutional neural networks. Nature Methods 20:.

Derry, A., Krzywinski, M. & Altman, N. (2023) Points of significance: Neural network primer. Nature Methods 20:165–167.

Lever, J., Krzywinski, M. & Altman, N. (2016) Points of significance: Logistic regression. Nature Methods 13:541–542.

# Neural network primer

Tue 10-01-2023

Nature is often hidden, sometimes overcome, seldom extinguished. —Francis Bacon

In the first of a series of columns about neural networks, we introduce them with an intuitive approach that draws from our discussion about logistic regression.

Nature Methods Points of Significance column: Neural network primer. (read)

Simple neural networks are just a chain of linear regressions. And, although neural network models can get very complicated, their essence can be understood in terms of relatively basic principles.

We show how neural network components (neurons) can be arranged in the network and discuss the ideas of hidden layers. Using a simple data set we show how even a 3-neuron neural network can already model relatively complicated data patterns.

Derry, A., Krzywinski, M & Altman, N. (2023) Points of significance: Neural network primer. Nature Methods 20:165–167.

Lever, J., Krzywinski, M. & Altman, N. (2016) Points of significance: Logistic regression. Nature Methods 13:541–542.

# Cell Genomics cover

Mon 16-01-2023

Our cover on the 11 January 2023 Cell Genomics issue depicts the process of determining the parent-of-origin using differential methylation of alleles at imprinted regions (iDMRs) is imagined as a circuit.

Designed in collaboration with with Carlos Urzua.

Our Cell Genomics cover depicts parent-of-origin assignment as a circuit (volume 3, issue 1, 11 January 2023). (more)

Akbari, V. et al. Parent-of-origin detection and chromosome-scale haplotyping using long-read DNA methylation sequencing and Strand-seq (2023) Cell Genomics 3(1).

Browse my gallery of cover designs.

A catalogue of my journal and magazine cover designs. (more)

Thu 05-01-2023

My cover design on the 6 January 2023 Science Advances issue depicts DNA sequencing read translation in high-dimensional space. The image showss 672 bases of sequencing barcodes generated by three different single-cell RNA sequencing platforms were encoded as oriented triangles on the faces of three 7-dimensional cubes.

My Science Advances cover that encodes sequence onto hypercubes (volume 9, issue 1, 6 January 2023). (more)

Kijima, Y. et al. A universal sequencing read interpreter (2023) Science Advances 9.

Browse my gallery of cover designs.

A catalogue of my journal and magazine cover designs. (more)

# Regression modeling of time-to-event data with censoring

Thu 17-08-2023

If you sit on the sofa for your entire life, you’re running a higher risk of getting heart disease and cancer. —Alex Honnold, American rock climber

In a follow-up to our Survival analysis — time-to-event data and censoring article, we look at how regression can be used to account for additional risk factors in survival analysis.

We explore accelerated failure time regression (AFTR) and the Cox Proportional Hazards model (Cox PH).

Nature Methods Points of Significance column: Regression modeling of time-to-event data with censoring. (read)

Dey, T., Lipsitz, S.R., Cooper, Z., Trinh, Q., Krzywinski, M & Altman, N. (2022) Points of significance: Regression modeling of time-to-event data with censoring. Nature Methods 19:1513–1515.

# Music video for Max Cooper's Ascent

Tue 25-10-2022

My 5-dimensional animation sets the visual stage for Max Cooper's Ascent from the album Unspoken Words. I have previously collaborated with Max on telling a story about infinity for his Yearning for the Infinite album.

I provide a walkthrough the video, describe the animation system I created to generate the frames, and show you all the keyframes

Frame 4897 from the music video of Max Cooper's Asent.

The video recently premiered on YouTube.

Renders of the full scene are available as NFTs.