The Maths4DL conference on Deep Learning for Computational Physics was hosted by University College London from 46 July 2023. The conference was open to the public and approximately 90 people attended in total. During the conference, participants heard from keynote and invited speakers, as well as short lightning talks from early career researchers and spent time networking during breaks. Slides from the talks will be available to download from these pages (programme and lightning talk sections) from speakers who are happy to share them.
The first day was opened by Prof Simon Arridge, UCL and after several talks from speakers, a poster session and drinks reception was held. Prizes (kindly donated by World Scientific Publishing and Springer) for the best posters were awarded to Pablo Arratia, Amir Ehsan Khorashadizadeh, Agnese Pacifico, and Victor Wang. Congratulations to you all!
The second day included further talks and discussion followed by the popular conference dinner at Drake & Morgan, Kings Cross. The final day’s talks concluded with a closing speech from Prof Chris Budd, University of Bath, Principal Investigator on the Maths4DL grant.
The overall feedback has been very positive, with over 90% of respondents rating the conference and the organisation of the conference as excellent or very good. Participants included PhD students, early career researchers, academics, plus some representatives from industry and truly represented the international nature of the work being carried out in the Maths4DL programme. Attendees came from towns and cities in Canada, England, Estonia, Finland, Germany, Italy, Japan, Netherlands, Norway, Saudi Arabia, Scotland, Sweden, Switzerland, USA and Wales.
We are already looking forward to our next conference, so watch this space!
Deep learning in physics represents a very active and rapidly growing field of research. This shift in approach has already brought with it many advances, which this meeting aims to highlight. Recent examples include PINNs, SINDy, symbolic regression, Fourier neural operators, metalearning, and neural ODEs to name a few. The applications also embrace many disciplines across the scientific spectrum, from medical sciences, to computer vision, to the physical sciences. We believe that the next steps for machine learning require a firm theoretical understanding and have organised this conference, taking place at UCL in central London, to bring together likeminded individuals to discuss current and future research in this area.
Included themes:
Places at the conference are now full but we are looking at ways to increase capacity. If you are still interested in registering, please email maths4dl@bath.ac.uk and we will keep you informed of our plans.
Please note, there are no longer places available at the conference dinner.
Tuesday 4th July  Wednesday 5th July  Thursday 6th July 
Arrival, registration, and refreshments  
Welcome and introduction – Prof. Simon Arridge  Arrival, registration, and refreshments  Arrival, registration, and refreshments 
Asst. Prof. Sophie Langer Understanding dropout in the linear world 
Prof. Giovanni S. Alberti Machine learning for infinitedimensional inverse problems 
Prof. Elena Celledoni A dynamical systems view to Deep learning: contractivity and structure preservation. 
Coffee break  Coffee break  Dr Marta Betcke Complementary learning in photoacoustic tomography 
Prof. Jason McEwen Geometric deep learning on the sphere for the physical sciences 
Dr Julián Tachella Learning to reconstruct images without groundtruth 
Coffee break 
Prof Andreas Hauptmann Modelcorrected learned primaldual models for fast limitedview photoacoustic tomography 
Dr Benjamin Moseley Scaling physicsinformed neural networks to high frequency and multiscale problems using domain decomposition 
Dr Cristopher Salvi Largewidth limits of neural ODEtype methods 
Lunch  Lunch  Lunch 
Dr Steve Brunton Machine Learning for Scientific Discovery, with Examples in Fluid Mechanics 
Prof Eldad Haber PDE’s, ODE’s Graphs and Neural Networks 
Dr Chris Rackauckas Generalizing Scientific Machine Learning and Differentiable Simulation Beyond Continuous Models 
Dr Zhi Zhou Identification of Conductivity in Elliptic equations using Deep Neural Networks 
Dr Nicolas Boulle Dataefficient PDE learning 
Emanuel Ström Acceleration of multiscale solvers via adjoint operator learning 
Coffee break  Coffee break  Coffee break 
Lightning talks  Janek Gödeke TorchPhysics: A Deep Learning Library for Solving Differential Equations 
Dr Patrick Kidger Scientific machine learning in JAX 
Dr Tatiana Bubba Integrating datadriven techniques and theoretical guarantees for limited angle tomography 
Prof. Michael Hintermüller Learninginformed and PINNbased multi scale PDE models in optimization 

16:3018:00, Poster session and drinks reception  16:3016:40, Summary and close, Prof. Chris Budd  
18:30late, Conference dinner at Drake & Morgan, Kings Cross. 
Dinner
The conference dinner will take place on Wednesday 5 July. The venue is Drake and Morgan, King Cross. You need to sign up and pay to attend the dinner when you register. You will be contacted nearer the time regarding your menu choices.
Travel
UCL is located in the Bloomsbury district at the very centre of London. There are easy connections to UCL from London’s global hub airports at Heathrow, Gatwick and Stansted and you will find that London’s extensive public transport system is convenient and easy to use.
The conference venue is marked on this map.
Further information about getting to UCL can be found here.
Accommodation
London has a wide variety of accommodation to suit all tastes and budgets. There are lots of options in and around Bloomsbury, close to the conference.
Below are a few hotels located nearby:
The Tavistock Hotel
Bloomsbury Palace hotel
Hub by Premier inn – Goodge Street
Gower House Hotel
Travelodge Euston
Euston Square Hotel
Royal National Hotel
Please note:
Accommodation is not included in the registration fee, delegates are required to book their own accommodation. We encourage delegates to book accommodation as early as possible.
Posters were presented by the following people. Click on their name for their slides and poster title for the poster pdf (where available).