2.2k citations · 2.5k across the 30 of their papers we have counts for
30 papers
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…
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…
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…
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…
Towards independent event horizon imaging of the supermassive black holes in M87 and the Milky Way
Nithyanandan Thyagarajan, Samuel Lai, Ivy Wong +1
The Event Horizon Telescope (EHT) Collaboration's images of the supermassive black holes in M87 and the Milky Way have provided the first event-horizon-scale views of these objects…
Conditional Image Diffusion with Interferometric Closure Invariants: Independent EHT Imaging of Centaurus~A and 3C~279
Samuel Lai, Nithyanandan Thyagarajan, O. Ivy Wong +1
We present independent imaging analyses of Event Horizon Telescope (EHT) observations of the active galactic nuclei in radio galaxy Centaurus~A and quasar 3C~279 using Generative D…
Very-Long Baseline Interferometry Imaging with Closure Invariants using Conditional Image Diffusion
Samuel Lai, Nithyanandan Thyagarajan, O. Ivy Wong +1
Image reconstruction in very-long baseline interferometry operates under severely sparse aperture coverage with calibration challenges from both the participating instruments and p…
Deep Learning VLBI Image Reconstruction with Closure Invariants
Samuel Lai, Nithyanandan Thyagarajan, O. Ivy Wong +2
Interferometric closure invariants, constructed from triangular loops of mixed Fourier components, capture calibration-independent information on source morphology. While a complet…
Tackling fluffy clouds: robust agricultural field boundary delineation from Sentinel-1 and Sentinel-2 satellite image time series
Foivos I. Diakogiannis, Zheng-Shu Zhou, Jeff Wang +13
Accurate delineation of agricultural field boundaries is essential for effective crop monitoring and resource management. However, competing methodologies often face significant ch…
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…
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…
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…
SSG2: A new modelling paradigm for semantic segmentation
Foivos I. Diakogiannis, Suzanne Furby, Peter Caccetta +4
State-of-the-art models in semantic segmentation primarily operate on single, static images, generating corresponding segmentation masks. This one-shot approach leaves little room…
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…
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…
Rapid localization of gravitational wave sources from compact binary coalescences using deep learning
Chayan Chatterjee, Manoj Kovalam, Linqing Wen +3
The mergers of neutron star-neutron star and neutron star-black hole binaries are the most promising gravitational wave events with electromagnetic counterparts. The rapid detectio…
Radio Transient Detection with Closure Products and Machine Learning
Xia Zhang, Foivos I. Diakogiannis, Richard Dodson +1
For transient sources with timescales of 1-100 seconds, standardized imaging for all observations at each time step become impossible as large modern interferometers produce signif…
Extraction of Binary Black Hole Gravitational Wave Signals from Detector Data Using Deep Learning
Chayan Chatterjee, Linqing Wen, Foivos Diakogiannis +1
Accurate extractions of the detected gravitational wave (GW) signal waveforms are essential to validate a detection and to probe the astrophysics behind the sources producing the G…
The ACTIONFINDER: An unsupervised deep learning algorithm for calculating actions and the acceleration field from a set of orbit segments
Rodrigo Ibata, Foivos Diakogiannis, Benoit Famaey +1
We introduce the "ACTIONFINDER", a deep learning algorithm designed to transform a sample of phase-space measurements along orbits in a static potential into action and angle coord…
Looking for change? Roll the Dice and demand Attention
Foivos I. Diakogiannis, François Waldner, Peter Caccetta
Change detection, i.e. identification per pixel of changes for some classes of interest from a set of bi-temporal co-registered images, is a fundamental task in the field of remote…
Deep learning on edge: extracting field boundaries from satellite images with a convolutional neural network
François Waldner, Foivos I. Diakogiannis
Applications of digital agricultural services often require either farmers or their advisers to provide digital records of their field boundaries. Automatic extraction of field bou…
ResUNet-a: a deep learning framework for semantic segmentation of remotely sensed data
Foivos I. Diakogiannis, François Waldner, Peter Caccetta +1
Scene understanding of high resolution aerial images is of great importance for the task of automated monitoring in various remote sensing applications. Due to the large within-cla…
Reliable mass calculation in spherical gravitating systems
Foivos I. Diakogiannis, Geraint F. Lewis, Rodrigo A. Ibata +3
We present an innovative approach to the methodology of dynamical modelling, allowing practical reconstruction of the underlying dark matter mass without assuming both the density…
Radio Galaxy Zoo: ClaRAN - A Deep Learning Classifier for Radio Morphologies
Chen Wu, O. Ivy Wong, Lawrence Rudnick +13
The upcoming next-generation large area radio continuum surveys can expect tens of millions of radio sources, rendering the traditional method for radio morphology classification t…