GitHub - GPBench/TinyverseGP Contribute to GPBench/TinyverseGP development by creating an account on GitHub.

TinyverseGP: Minimalistic implementations of different representations for Genetic Programming github.com/gpbench/tiny... #mlsky #artificialintelligence #geneticprogramming

Report on the Royal Society Discussion Meeting on Symbolic Regression in… | Gabriel Kronberger Here is my summary of the Symbolic Regression in Physical Sciences meeting (together with Fabricio Olivetti de França and Bogdan Burlacu). My three take-home messages: 🧐 Better priors and additiona...

Here's a little summary of the #symbolicregression in Physical Sciences meeting hosted at the #royalsociety . Plenty of interesting discussions and perspectives for the future of SR: www.linkedin.com/posts/gabrie...

This new algorithm pairs well with another tool we just released bsky.app/profile/foli...

rEGGression: an Interactive and Agnostic Tool for the Exploration of Symbolic Regression Models Regression analysis is used for prediction and to understand the effect of independent variables on dependent variables. Symbolic regression (SR) automates the search for non-linear regression models,...

This paper will be presented at #GECCO2025 but you can already read the pre-print at arxiv.org/abs/2501.17859

The source-code and binaries are available at github.com/folivetti/sr... together with additional info.

#GECCO2025 #SymbolicRegression #GeneticProgramming

This tool is compatible with a lot of popular SR algorithms such as 𝐎𝐩𝐞𝐫𝐨𝐧, 𝐏𝐲𝐒𝐑, 𝐁𝐢𝐧𝐠𝐨, 𝐅𝐄𝐀𝐓, 𝐈𝐓𝐄𝐀, 𝐓𝐈𝐑, 𝐆𝐏-𝐆𝐎𝐌𝐄𝐀, and many more!

It is especially compatible with the new algorithm eggp (bsky.app/profile/foli...)

rEGGression demo - a tool for the exploration of symbolic regression models *r🥚ression* an interactive tool that can help SR users to explore alternative models generated from different sources. These sources can be: the final population of a single run, the Pareto front, ...

You can also search for the top building blocks by frequency and average fitness. This can help unlock new discoveries from the knowledge built during the search.

A little demo of what it can do:

asciinema.org/a/713509

Once you load the expressions, you can explore them by requesting the top-N expressions associated with different filters: by size, by number of parameters or ... 𝐛𝐲 𝐩𝐚𝐭𝐭𝐞𝐫𝐧 𝐦𝐚𝐭𝐜𝐡𝐢𝐧𝐠 parts of the expressions!

With this tool, you can load a set of symbolic models obtained from any combination of multiple runs from the same or different algorithms, or with different hyper-parameters, using only the returned Pareto front or the entire search history.

⚠️(another) New paper alert

rEGGression: an Interactive and Agnostic Tool for the Exploration of Symbolic Regression Models introduces a new tool for symbolic models that allow the user to go beyond the traditional Pareto front.
#GECCO2025 #SymbolicRegression #GeneticProgramming

This work will be presented at #GECCO2025 but we already got an arXiv version available at arxiv.org/abs/2501.17848 and the source-code at github.com/folivetti/sr...

All the experiments can be replicated with github.com/folivetti/eg...

This improves the results to such an extent that a traditional GP (as in tinyGP) can compete with the popular Operon and PySR algorithms.

The current implementation comes with many customization options including exporting the generated e-graph for further exploration.

For example, if in the first generation the search visits the expression (x+x) it will avoid generating this expression again in future generations and most of their equivalents, such as 2x, 3x/x, 3x - x, etc.

⚠️New paper alert ⚠️

Improving Genetic Programming for Symbolic Regression with Equality Graphs exploits e-graphs to generate equivalent expressions proposes new operators that creates unvisited expressions during the search.

#GECCO2025 #SymbolicRegression #GeneticProgramming

Time is on your side? Yes it is!
The deadline for the #symbolicregression workshop at #gecco2025, was just extended to April 2nd! We are looking forward for your submissions! More info: heal.heuristiclab.com/research/sym...

You are all preparing some cool papers for #symbolicregression workshop at #gecco2025, right? Just remember, the deadline is on March 26! Share your new and cool ideas with this ever growing community! More info: heal.heuristiclab.com/research/sym...

Tell me about it :-D We're currently fighting to split the course into CS and non-CS version. But I'm already happy that we don't teach this course in Java anymore :-P

The main challenge here is to make them understand how a function works, what are variables, and why the order of instructions matter :-) not the easiest of the courses to teach...

Here we have the course "Information Processing" (which I'm teaching right now) that is basically programming 101 for a mix of students (CS and non-CS). The main goal here is to teach the very basics so each student is prepared to learn their respective niche language when time comes.

5 PhD positions for a project on Wireless THz Communication between TU Wien and University of Applied Sciences Upper Austria. One of such positions is about equation learning with #symbolicregression . Don't miss this opportunity! More info: jobs.tuwien.ac.at/Job/246521

I feel the same, and not only as a reviewer, as an author as well, especially when we get good reviewers :)

Is the evolution metaphor still necessary or even useful for genetic programming? - Genetic Programming and Evolvable Machines Genetic Programming and Evolvable Machines -

Is the evolution metaphor still necessary or even useful for genetic programming? link.springer.com/article/10.1... #geneticprogramming #machinelearning #artificialintelligence #datascience

We have a date! #symbolicregression workshop at #gecco2025 now has a deadline: March 26. Be sure to share your cool ideas with us heal.heuristiclab.com/research/sym...

Meeting on “Symbolic Regression in the Physical Sciences”.

Date: 28 - 29 April 2025,
Location: The Royal Society, 6 – 9 Carlton House Terrace, London, SW1Y 5AG

Details and registration:

royalsociety.org/science-even...

is it really useful in practice to have explicit feature transformation in these templates? (e.g. f(x1^2,x1*x2)). It seems to me that the user is doing the SR job :-P Wouldn't a syntax like `p1 * x1 + f1 - sin(f2)` be enough and cleaner?

Hey #symbolicregression folks! Are you working on something novel, crazy, bound to uncover the secrets of the universe? Don't keep it to yourself, join us at #gecco2025 SymReg workshop and let's discuss it over a coffee: heal.heuristiclab.com/research/sym... (deadline tbd) #geneticprogramming

This looks really cool!