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k4v1t · MATHEMATICS · AI · SCIENCE

Working things out, visually

This site is a collection of visual explanations, interactive experiments, research notes and projects exploring mathematics, machine learning and scientific inference.

I am especially interested in what models are actually learning from data, where ambiguity remains, and how visualisation can make difficult ideas easier to reason about.

Some pieces explain ideas I have found useful; others are questions I am still working through.

Explore the visual essays

Explore

Interactive essays

Visual explanations and experiments that let you adjust parameters, test assumptions and see how a system changes.

Browse the essays

Research

Research on scientific machine learning, inverse problems and related areas.

Coming soon

Publications

Papers, preprints and other formally published work.

Coming soon

Projects & notes

Code, technical experiments and shorter explorations of ideas that are still developing.

Coming soon

Selected work

There is no hidden text

An interactive visual essay about how statistical watermarks can hide in the choices a language model makes.

Artificial Intelligence · Language Models · Watermarking · Interactive

When different black-hole binaries look the same

An interactive exploration of parameter degeneracies in gravitational-wave inference.

Gravitational waves · Inverse problems · Interactive

More explorations to come

This site will grow gradually as I turn research questions, mathematical ideas and useful explanations into interactive essays.

Work In Progress · Learning in Public

Current themes

The work here will mostly sit around scientific machine learning, inverse problems, mathematical intuition and the question of what can (or cannot) be learned from data.

I am more interested in developing better questions than presenting polished answers.

More about me

Source Code
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k4v1t · MATHEMATICS · AI · SCIENCE
:::

# Working things out, visually

This site is a collection of visual explanations, interactive experiments, research notes and projects exploring mathematics, machine learning and scientific inference.

I am especially interested in what models are actually learning from data, where ambiguity remains, and how visualisation can make difficult ideas easier to reason about.

Some pieces explain ideas I have found useful; others are questions I am still working through.

[Explore the visual essays](essays.qmd){.btn .btn-primary .btn-lg}
:::

## Explore

::: {.featured-grid}
::: {.featured-card}

### Interactive essays

Visual explanations and experiments that let you adjust parameters, test assumptions and see how a system changes.

[Browse the essays](essays.qmd)
:::

::: {.featured-card}

### Research

Research on scientific machine learning, inverse problems and related areas.

`Coming soon`
:::

::: {.featured-card}

### Publications

Papers, preprints and other formally published work.

`Coming soon`
:::

::: {.featured-card}

### Projects & notes

Code, technical experiments and shorter explorations of ideas that are still developing.

`Coming soon`
:::
:::

## Selected work

::: {.featured-grid}

::: {.featured-card}

### [There is no hidden text](posts/claude-watermark/index.qmd)

An interactive visual essay about how statistical watermarks can hide in the choices a language model makes.

`Artificial Intelligence` · `Language Models` · `Watermarking` · `Interactive`
:::

::: {.featured-card}

### [When different black-hole binaries look the same](posts/mbhb-redundancies/index.qmd)

An interactive exploration of parameter degeneracies in gravitational-wave inference.

`Gravitational waves` · `Inverse problems` · `Interactive`
:::

:::

### More explorations to come

This site will grow gradually as I turn research questions, mathematical ideas and useful explanations into interactive essays.

`Work In Progress` · `Learning in Public`

## Current themes

The work here will mostly sit around scientific machine learning, inverse problems, mathematical intuition and the question of what can (or cannot) be learned from data.

I am more interested in developing better questions than presenting polished answers.

[More about me](about.qmd)

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