Rory Byrne

Rory Byrne

@rory.bio

Neuroscience PhD student, Cambridge UK. Confused but excited. "Everything around me was somebody's lifework" 👋 https://rory.bio 🔧 https://compmotifs.com/

541 followers1.4K following74 posts

Rory Byrne reposted

Toy models, just in time for Christmas! Excited to share my first article for @thetransmitter.bsky.social #neuroskyence

The Transmitter @thetransmitter.bsky.social

Amid the rise of billion-parameter models, I argue that toy models, with just a few neurons, remain essential—and may be all neuroscience needs, writes @marcusghosh.bsky.social. #neuroskyence www.thetransmitter.org/theoretical-...

Answer: because seniors know the language of software architecture. This enriches their LLM prompting significantly. If you want to successfully use AI for coding, learn some software architecture!

Proud to have been a part of this, a great example of distributed async science! Huge thanks to @marcusghosh.bsky.social, @neuralreckoning.bsky.social, @tfiers.bsky.social, @krhab.bsky.social and others for putting in the bulk effort 🙌

Dan Goodman@neural-reckoning.org

Is anarchist science possible? As an experiment, we got together a large group of computational neuroscientists from around the world to work on a single project without top down direction. Read on to find out what happened. 🤖🧠🧪

Rory Byrne reposted

Rory Byrne reposted

Come build tools for science with us in London! Food, cool people, great speakers (on both the science and toolmaking sides). #neuroskyence #openscience #desci #openchem #bioinformatics #opensource #foss

Wojtek Treyde@wtreyde.bsky.social

​Following our successful SF event, we (www.compmotifs.com) are running another hackathon! When? 7-8 June. Where? London, UK. Who? Builders and researchers from academia and industry. What? Develop innovative computational tools to advance the natural sciences. Join us: lu.ma/apsqlxlj?utm....

Rory Byrne reposted

How can we explore the space of computational models in #neuroscience 🧠? Picture a mouse navigating an environment with light and dark areas. 🧵1/10

Pablo Samuel Castro@pcastr.bsky.social

Can LLMs be used to discover interpretable models of human and animal behavior?🤔 Turns out: yes! Thrilled to share our latest preprint where we used FunSearch to automatically discover symbolic cognitive models of behavior. 1/12

If you’re in SF, come build tools-for-science with us later this month! 🛠️ #opensource #neuroskyence #openscience #machinelearning #compchem #chemsky

Wojtek Treyde@wtreyde.bsky.social

We (www.compmotifs.com) are coming to SF! Together with Pebblebed, we’re hosting a 2-day hackathon on 26-27 March for builders and scientists across disciplines to build new methods and tools for the computational and natural sciences. Join us: lu.ma/t5yik06g. Reposts will be much appreciated!

Rory Byrne reposted

#opensource #python #openscience #neuroskyence #machinelearning #neuroai

Rory Byrne@rory.bio

🔧 Logis - turn your git history into a searchable scientific log. The `@commit` decorator auto-commits your code when your experiment runs - with metadata in the message. Then you can find previous results by querying for commits with (e.g.) metrics.accuracy > 0.9. github.com/flywhl/logis

View full thread
View full thread

Then when your experiment runs, logis will commit your code for you, with a nice commit message and experiment metadata at the bottom.

View full thread
View full thread

You can also pre-process the raw data using @hooks. The @env:MY_VARIABLE hook loads data from an environment variable. The @value:path.to.val hook references a value in the raw input data. The @import:foo.bar dynamically imports a Python object.

The idea is simple: write an object's Blueprint once, then whenever you need that object in your @pydantic.dev models, just pass in the parameters. In #machinelearning and #neuroai, we build a lot of Tensors from various parameterisations...

"Scientific code is too intricate, and requires human attention." A huge amount of variance in scientific code is self-imposed noise. How many bugs boil down to getting the dimensions of a matrix wrong? Code generation means that those decisions are made for you.

Dimension errors are the "missing semi-colon" of scientific code. They cause an inordinate amount of pain, but can be solved trivially with post-processing of code.

Nice to see journals thinking about software tools, but I wonder if they can offer more to toolmakers than “here is a place to re-write your README in more opaque language”?

eLife@elife.bsky.social

🛠️ November's most-read Tools and Resources paper presents a new method to identify dynamic causal interactions in complex systems: https://buff.ly/3Zldxpt Learn more about publishing your tools or resources with us: https://buff.ly/4f2O0Ht

Rory Byrne reposted

If you work with Python dataframes (pandas, @pola.rs) and are not using skrub.TableReport, you're missing out 😀 We keep improving it

Skrub@skrub-data.bsky.social

A new version of skrub is out! skrub 0.4.1 fixes some issues with the TableReport and the tabular_learner, fills some gaps in the documentation, and ensures compatibility with the latest scikit-learn version (1.6). Changelog: skrub-data.org/stable/CHANG...

And if my grandmother had wheels she’d be a bicycle.

PessoaBrain@pessoabrain.bsky.social

This would be funny if it weren't sad... Coming from the "giants" of AI. Or maybe this was posted out of context? Please clarify. I can't process this...