Welcome to Dan’s brain

The contents of my head are not useful if they stay in there, so I regularly copy-paste them onto the internet, into this very website. Here you can find most of the things I am thinking about, in the form of a higgledy heap of half-finished notebooks and occasional polished essays. Themes include whatever shiny thing distracted me into taking notes about it, including, but not limited to,

You might be after information about me generally, or what I am doing right now.

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Generative art with language+diffusion models

buzzword
computers are awful
generative art
machine learning
making things
music
neural nets
photon choreography
UI

Code generation, programming assistants

faster pussycat
language
machine learning
making things
neural nets
NLP
signal processing
stringology
UI

Free images

content
making things
photon choreography

Neural nets that do symbolic mathematics, logic and other reasoning tasks

compsci
language
machine learning
meta learning
networks
neural nets
NLP
stringology

Syncthing

computers are awful
computers are awful together
concurrency hell
distributed
diy
P2P

Causal abstraction

approximation
Bayes
causal
generative
graphical models
language
machine learning
meta learning
neural nets
NLP
probabilistic algorithms
probability
statistics
stringology
time series

Mechanistic interpretability

adversarial
classification
communicating
feature construction
statmech
stochastic processes
high d
language
machine learning
metrics
mind
NLP
sparser than thou

Developmental interpretability

adversarial
Bayes
classification
dynamical systems
feature construction
high d
language
machine learning
metrics
mind
NLP
sparser than thou
statmech
stochastic processes

Research discovery and synthesis

academe
collective knowledge
faster pussycat
how do science
institutions
mind
networks
provenance
sociology
wonk

Multi agent causality

adaptive
agents
causal
cooperation
economics
evolution
extended self
game theory
graphical models
incentive mechanisms
learning
mind
networks
social graph
utility
wonk

Neural PDE operator learning on domains with interesting geometry

calculus
dynamical systems
geometry
Hilbert space
how do science
Lévy processes
machine learning
neural nets
PDEs
physics
regression
sciml
SDEs
signal processing
statistics
statmech
stochastic processes
surrogate
time series
uncertainty

Neural PDE operator learning

calculus
dynamical systems
geometry
Hilbert space
how do science
Lévy processes
machine learning
neural nets
PDEs
physics
regression
sciml
SDEs
signal processing
statistics
statmech
stochastic processes
surrogate
time series
uncertainty

The AI tech soap opera

agents
bounded compute
collective knowledge
economics
edge computing
extended self
faster pussycat
incentive mechanisms
innovation
language
machine learning
neural nets
NLP
swarm
technology
UI
when to compute

Feed readers

academe
computers are awful together
doing internet
faster pussycat
learning
provenance
UI
workflow

Learning with conservation laws, invariances and symmetries

algebra
how do science
information
machine learning
networks
physics
probability
sciml
statistics
statmech

Git tricks

computers are awful
provenance
workflow

Human domestication

agents
cooperation
culture
distributed
economics
evolution
extended self
incentive mechanisms
language
mind
utility
wonk

Causality, agency, decisions

adaptive
agents
causal
cooperation
economics
evolution
extended self
game theory
graphical models
incentive mechanisms
learning
mind
networks
social graph
utility
wonk

Aligning AI systems

adversarial
classification
communicating
feature construction
game theory
high d
language
machine learning
metrics
mind
NLP

Contemporary rationalists

catastrophe
culture
ethics
history
language
mind
wonk

Leadership

incentive mechanisms
institutions
mind
wonk

Reading ebooks

academe
computers are awful
faster pussycat
learning
provenance
UI
workflow

Computational complexity of Bayesian inference

Bayes
how do science
statistics

Neural PDE operator learning using transformers

calculus
dynamical systems
geometry
Hilbert space
how do science
Lévy processes
machine learning
neural nets
PDEs
physics
regression
sciml
SDEs
signal processing
statistics
statmech
stochastic processes
surrogate
time series
uncertainty

Adaptive design of experiments

functional analysis
how do science
model selection
optimization
surrogate
when to compute

Australia in data

data sets
place
Southeast Asia
straya

Data sets for machine learning for partial differential equations

calculus
data sets
dynamical systems
geometry
machine learning
neural nets
PDEs
physics
regression
sciml
SDEs
signal processing
statistics
statmech
stochastic processes
surrogate
time series

Causal Bayesian networks via probability trees

algebra
causal
graphical models
how do science
machine learning
measure
networks
probability
statistics

Travel hacks

faster pussycat
money
travel

Inference from disorder

causal
compsci
dynamical systems
networks
physics
probability
pseudorandomness
statistics
statmech
stochastic processes

Garbled highlights from ICLR 2025

neural nets
South East Asia
statistics

Artificial agency

adaptive
agents
cooperation
economics
evolution
extended self
game theory
incentive mechanisms
learning
mind
networks
utility
wonk

Neural codecs and compression algorithms

compsci
computers are awful
information
metrics
music
photon choreography
standards

Machine learning for partial differential equations via flows

calculus
dynamical systems
geometry
Hilbert space
how do science
Lévy processes
machine learning
neural nets
PDEs
physics
regression
sciml
SDEs
signal processing
statistics
statmech
stochastic processes
surrogate
time series
uncertainty

Machine learning for partial differential equations using diffusion models

calculus
dynamical systems
geometry
Hilbert space
how do science
Lévy processes
machine learning
neural nets
PDEs
physics
regression
sciml
SDEs
signal processing
statistics
statmech
stochastic processes
surrogate
time series
uncertainty

Causal inference on DAGs

algebra
causal
graphical models
how do science
machine learning
networks
probability
statistics

Scaling laws for very large neural nets

bounded compute
functional analysis
machine learning
model selection
optimization
statmech
when to compute

Bayesian and causal inference by foundation models

approximation
Bayes
causal
generative
language
machine learning
meta learning
Monte Carlo
neural nets
NLP
optimization
probabilistic algorithms
probability
statistics
stringology
time series

Neural denoising diffusion models

approximation
Bayes
generative
Monte Carlo
neural nets
optimization
probabilistic algorithms
probability
score function
statistics

Data summarization

approximation
estimator distribution
functional analysis
information
linear algebra
model selection
optimization
probabilistic algorithms
probability
signal processing
sparser than thou
statistics
when to compute

Extraversion

communicating
cooperation
gene
health
learning
mind
neuron
personality
utility

ML benchmarks and their pitfalls

economics
game theory
how do science
incentive mechanisms
institutions
machine learning
neural nets
statistics

Causal inference under feedback

algebra
causal
graphical models
how do science
machine learning
networks
neural nets
probability
statistics
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