activity
20222026
most citedDeep symbolic regression for physics guided by units constraints: toward the automated discovery of physical laws

112 citations · 151 across the 13 of their papers we have counts for

collaborators

13 papers

cs.LG2026

Do Tabular Foundation Models Know Physics? Contamination, Units, and the Deterministic Limit

Wassim Tenachi, Yashar Hezaveh, Laurence Perreault Levasseur +1

Tabular foundation models (TFMs) learn to fill in tables the way language models fill in text --- and tables are arguably the format in which most physical measurement arrives. Did…

astro-ph.IM2026

NestyNet. IV. Laws Chosen by Nothing in Advance

Rodrigo Ibata, Wassim Tenachi, Foivos Diakogiannis +2

Differential-equation (DE) discovery tends to break down precisely where much of physics begins. Fields are coupled, governing laws are nonlinear in the state, amplitudes, coordina…

astro-ph.IM2026

NestyNet. III. Symbolic Regression from Analytic Neural Surrogates

Rodrigo Ibata, Wassim Tenachi, Foivos Diakogiannis +2

Many physical laws are simple only after the right representation, decomposition or internal coordinate has been found, but discovering that structure from data is combinatorially…

astro-ph.IM2026

NestyNet. II. Coherent Function-Space Posteriors from Scientific Neural Surrogates (or How to Avoid Expensive MCMC)

Rodrigo Ibata, Wassim Tenachi, Foivos Diakogiannis +2

Scientific analyses increasingly use flexible neural networks, but their thousands of correlated parameters make it challenging to interpret the associated uncertainties. Here we d…

astro-ph.IM2026

NestyNet. I. Physics Functions Are Hard to Fit with Neural Networks: A Framework for Accurate Surrogates and Analytic Derivatives

Rodrigo Ibata, Wassim Tenachi, Foivos Diakogiannis +2

Many of the smooth functions that matter most in physics are precisely the ones that standard neural network methods struggle to fit accurately. Here we present NestyNet, a coupled…

math.NA2024★ 2 cited

Generalizing the SINDy approach with nested neural networks

Camilla Fiorini, Clément Flint, Louis Fostier +4

Symbolic Regression (SR) is a widely studied field of research that aims to infer symbolic expressions from data. A popular approach for SR is the Sparse Identification of Nonlinea…

cs.LG2023★ 2 cited

Physical Symbolic Optimization

Wassim Tenachi, Rodrigo Ibata, Foivos I. Diakogiannis

We present a framework for constraining the automatic sequential generation of equations to obey the rules of dimensional analysis by construction. Combining this approach with rei…

cs.LG2023★ 2 cited

Class Symbolic Regression: Gotta Fit 'Em All

Wassim Tenachi, Rodrigo Ibata, Thibaut L. François +1

We introduce 'Class Symbolic Regression' (Class SR) a first framework for automatically finding a single analytical functional form that accurately fits multiple datasets - each re…

astro-ph.GA2023★ 1 cited

Charting the Galactic acceleration field II. A global mass model of the Milky Way from the STREAMFINDER Atlas of Stellar Streams detected in Gaia DR3

Rodrigo Ibata, Khyati Malhan, Wassim Tenachi +17

We present an atlas and follow-up spectroscopic observations of 87 thin stream-like structures detected with the STREAMFINDER algorithm in Gaia DR3, of which 29 are new discoveries…

astro-ph.GA2023

An end-to-end strategy for recovering a free-form potential from a snapshot of stellar coordinates

Wassim Tenachi, Rodrigo Ibata, Foivos I. Diakogiannis

New large observational surveys such as Gaia are leading us into an era of data abundance, offering unprecedented opportunities to discover new physical laws through the power of m…

astro-ph.IM2023★ 112 cited

Deep symbolic regression for physics guided by units constraints: toward the automated discovery of physical laws

Wassim Tenachi, Rodrigo Ibata, Foivos I. Diakogiannis

Symbolic Regression is the study of algorithms that automate the search for analytic expressions that fit data. While recent advances in deep learning have generated renewed intere…

astro-ph.GA2022★ 15 cited

Antaeus: a retrograde group of tidal debris in the Milky Way's disk plane

Pierre-Antoine Oria, Wassim Tenachi, Rodrigo Ibata +5

We present the discovery of a wide retrograde moving group in the disk plane of the Milky Way using action-angle coordinates derived from the \textit{Gaia} DR3 catalog. The structu…

astro-ph.GA2022★ 17 cited

Typhon: a polar stream from the outer halo raining through the Solar neighborhood

Wassim Tenachi, Pierre-Antoine Oria, Rodrigo Ibata +5

We report on the discovery in the Gaia DR3 astrometric and spectroscopic catalog of a new polar stream that is found as an over-density in action space. This structure is unique as…