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Workshop

Machine Learning and the Physical Sciences

Atilim Gunes Baydin ⋅ Adji Bousso Dieng ⋅ Emine Kucukbenli ⋅ Gilles Louppe ⋅ Siddharth Mishra-Sharma ⋅ Benjamin Nachman ⋅ Brian Nord ⋅ Savannah Thais ⋅ Anima Anandkumar ⋅ Kyle Cranmer ⋅ Lenka Zdeborová ⋅ Rianne van den Berg
Project Page [ Contact: [email protected] ]

Abstract

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Schedule

Timezone: America/Los_Angeles
5:50 AM
Opening remarks
10:00 AM
Lunch
11:15 AM
Invited talk: E. Doğuş Çubuk, "Scaling up material discovery via deep learning"
Ekin Dogus Cubuk ⋅ Siddharth Mishra-Sharma
1:15 PM
Break
1:30 PM
Invited talk: Catherine Nakalembe and Hannah Kerner
Catherine Nakalembe ⋅ Hannah Kerner ⋅ Siddharth Mishra-Sharma
2:00 PM
Closing remarks
Leveraging the Stochastic Predictions of Bayesian Neural Networks for Fluid Simulations
Maximilian Mueller ⋅ Robin Greif ⋅ Frank Jenko ⋅ Nils Thuerey
Discovering Long-period Exoplanets using Deep Learning with Citizen Science Labels
Shreshth A Malik ⋅ Nora Eisner ⋅ Chris Lintott ⋅ Yarin Gal
Virgo: Scalable Unsupervised Classification of Cosmological Shock Waves
Max Lamparth ⋅ Ludwig Böss ⋅ Ulrich Steinwandel ⋅ Klaus Dolag
Learning Feynman Diagrams using Graph Neural Networks
Alexander Norcliffe ⋅ Harrison Mitchell ⋅ Pietro Lió
Certified data-driven physics-informed greedy auto-encoder simulator
Xiaolong He ⋅ Youngsoo Choi ⋅ William Fries ⋅ Jon Belof ⋅ Jiun-Shyan Chen
Offline Model-Based Reinforcement Learning for Tokamak Control
Ian Char ⋅ Joseph Abbate ⋅ Laszlo Bardoczi ⋅ Mark Boyer ⋅ Youngseog Chung ⋅ Rory Conlin ⋅ Keith Erickson ⋅ Viraj Mehta ⋅ Nathan Richner ⋅ Egemen Kolemen ⋅ Jeff Schneider
Decay-aware neural network for event classification in collider physics
Tomoe Kishimoto ⋅ Masahiro Morinaga ⋅ Masahiko Saito ⋅ Junichi Tanaka
Lyapunov Regularized Forecaster
Rong Zheng ⋅ Rose Yu
Molecular Fingerprints for Robust and Efficient ML-Driven Molecular Generation
Ruslan Tazhigulov ⋅ Joshua Schiller ⋅ Jacob Oppenheim ⋅ Max Winston
Machine Learning for Chemical Reactions \\A Dance of Datasets and Models
Mathias Schreiner ⋅ Arghya Bhowmik ⋅ Tejs Vegge ⋅ Jonas Busk ⋅ Peter Bjørn Jørgensen ⋅ Ole Winther
ML4LM: Machine Learning for Safely Landing on Mars
David Wu ⋅ Wai Tong Chung ⋅ Matthias Ihme
Flexible learning of quantum states with generative query neural networks
Yan Zhu ⋅ Ya-Dong Wu ⋅ Ge Bai ⋅ Dong-Sheng Wang ⋅ Yuexuan Wang ⋅ Giulio Chiribella
Transfer Learning with Physics-Informed Neural Networks for Efficient Simulation of Branched Flows
Raphael Pellegrin ⋅ Blake Bullwinkel ⋅ Marios Mattheakis ⋅ Pavlos Protopapas
Decorrelation with Conditional Normalizing Flows
Samuel Klein ⋅ Tobias Golling
Training physical networks like neural networks: deep physical neural networks
Logan Wright ⋅ Tatsuhiro Onodera ⋅ Martin M Stein ⋅ Tianyu Wang ⋅ Darren Schachter ⋅ Zoey Hu ⋅ Peter McMahon
Learning latent variable evolution for the functional renormalization group
Matija Medvidović ⋅ Alessandro Toschi ⋅ Giorgio Sangiovanni ⋅ Cesare Franchini ⋅ Andy Millis ⋅ Anirvan Sengupta ⋅ Domenico Di Sante
Deformations of Boltzmann Distributions
Bálint Máté ⋅ François Fleuret
Neuro-Symbolic Partial Differential Equation Solver
Pouria Akbari Mistani ⋅ Samira Pakravan ⋅ Rajesh Ilango ⋅ Sanjay Choudhry ⋅ Frederic Gibou
Generating astronomical spectra from photometry with conditional diffusion models
Lars Doorenbos ⋅ Stefano Cavuoti ⋅ Giuseppe Longo ⋅ Massimo Brescia ⋅ Raphael Sznitman ⋅ Pablo Márquez Neila
Identifying AGN host galaxies with convolutional neural networks
Ziting Guo ⋅ John Wu ⋅ Chelsea Sharon
Machine learning for complete intersection Calabi-Yau manifolds
Harold Erbin ⋅ Mohamed Tamaazousti ⋅ Riccardo Finotello
SuNeRF: Validation of a 3D Global Reconstruction of the Solar Corona Using Simulated EUV Images
Kyriaki-Margarita Bintsi ⋅ Robert Jarolim ⋅ Benoit Tremblay ⋅ Miraflor Santos ⋅ Anna Jungbluth ⋅ James Mason ⋅ Sairam Sundaresan ⋅ Angelos Vourlidas ⋅ Cooper Downs ⋅ Ronald Caplan ⋅ Andres Munoz-Jaramillo
Generating Calorimeter Showers as Point Clouds
Simon Schnake ⋅ Dirk Krücker ⋅ Kerstin Borras
Physics solutions for privacy leaks in machine learning
Alejandro Pozas-Kerstjens ⋅ Senaida Hernandez-Santana ⋅ José Ramón Pareja Monturiol ⋅ Marco Castrillon Lopez ⋅ Giannicola Scarpa ⋅ Carlos E. Gonzalez-Guillen ⋅ David Perez-Garcia
Simplifying Polylogarithms with Machine Learning
Aurelien Dersy ⋅ Matthew Schwartz ⋅ Xiaoyuan Zhang
NLP Inspired Training Mechanics For Modeling Transient Dynamics
Lalit Ghule ⋅ Rishikesh Ranade ⋅ Jay Pathak
Reducing Down(stream)time: Pretraining Molecular GNNs using Heterogeneous AI Accelerators
Jenna A Bilbrey ⋅ Kristina Herman ⋅ Henry Sprueill ⋅ Sotiris Xantheas ⋅ Payel Das ⋅ Manuel Lopez Roldan ⋅ Mike Kraus ⋅ Hatem Helal ⋅ Sutanay Choudhury
Emulating Fast Processes in Climate Models
Noah Brenowitz ⋅ W. Andre Perkins ⋅ Jacqueline M. Nugent ⋅ Oliver Watt-Meyer ⋅ Spencer K. Clark ⋅ Anna Kwa ⋅ Brian Henn ⋅ Jeremy McGibbon ⋅ Christopher S. Bretherton
GAUCHE: A Library for Gaussian Processes in Chemistry
Ryan-Rhys Griffiths ⋅ Leo Klarner ⋅ Henry Moss ⋅ Aditya Ravuri ⋅ Sang Truong ⋅ Bojana Rankovic ⋅ Yuanqi Du ⋅ Arian Jamasb ⋅ Julius Schwartz ⋅ Austin Tripp ⋅ Gregory Kell ⋅ Anthony Bourached ⋅ Alex Chan ⋅ Jacob Moss ⋅ Chengzhi Guo ⋅ Alpha Lee ⋅ Philippe Schwaller ⋅ Jian Tang
One-shot learning for solution operators of partial differential equations
Lu Lu ⋅ Anran Jiao ⋅ Jay Pathak ⋅ Rishikesh Ranade ⋅ Haiyang He
Qubit seriation: Undoing data shuffling using spectral ordering
Atithi Acharya ⋅ Manuel Rudolph ⋅ Jing Chen ⋅ Jacob Miller ⋅ Alejandro Perdemo-Ortiz
First principles physics-informed neural network for quantum wavefunctions and eigenvalue surfaces
Marios Mattheakis ⋅ Gabriel R. Schleder ⋅ Daniel Larson ⋅ Efthimios Kaxiras
Renormalization in the neural network-quantum field theory correspondence
Harold Erbin ⋅ Vincent Lahoche ⋅ Dine Ousmane Samary
Applying Deep Reinforcement Learning to the HP Model for Protein Structure Prediction
Kaiyuan Yang ⋅ Houjing Huang ⋅ Olafs Vandans ⋅ Adithyavairavan Murali ⋅ Fujia Tian ⋅ Roland Yap ⋅ Liang Dai
Intra-Event Aware Imitation Game for Fast Detector Simulation
Hosein Hashemi ⋅ Nikolai Hartmann ⋅ Sahand Sharifzadeh ⋅ James Kahn ⋅ Thomas Kuhr
Deep Learning Modeling of Subgrid Physics in Cosmological N-body Simulations
Georgios Markos Chatziloizos ⋅ Francois Lanusse ⋅ Tristan Cazenave
Point Cloud Generation using Transformer Encoders and Normalising Flows
Benno Käch ⋅ Dirk Krücker ⋅ Isabell Melzer
Simulation-based inference of the 2D ex-situ stellar mass fraction distribution of galaxies using variational autoencoders
Eirini Angeloudi ⋅ Marc Huertas-Company ⋅ Jesús Falcón-Barroso ⋅ Regina Sarmiento ⋅ Daniel Walo-Martín ⋅ Annalisa Pillepich ⋅ Jesús Vega Ferrero
Uncertainty quantification methods for ML-based surrogate models of scientific applications
Kishore Basu ⋅ Yujia Hao ⋅ Delphine Hintz ⋅ Dev Shah ⋅ Aaron Palmer ⋅ Gurpreet Singh Hora ⋅ Darian Nwankwo ⋅ Laurent White
Contrasting random and learned features in deep Bayesian linear regression
Jacob Zavatone-Veth ⋅ William Tong ⋅ Cengiz Pehlevan
Semi-Supervised Domain Adaptation for Cross-Survey Galaxy Morphology Classification and Anomaly Detection
Aleksandra Ciprijanovic ⋅ Ashia Lewis ⋅ Kevin Pedro ⋅ Sandeep Madireddy ⋅ Brian Nord ⋅ Gabriel Nathan Perdue ⋅ Stefan Wild
A Neural Network Subgrid Model of the Early Stages of Planet Formation
Thomas Pfeil ⋅ Miles Cranmer ⋅ Shirley Ho ⋅ Philip Armitage ⋅ Tilman Birnstiel ⋅ Hubert Klahr
Validation Diagnostics for SBI algorithms based on Normalizing Flows
Julia Linhart ⋅ Alexandre Gramfort ⋅ Pedro Rodrigues
One Network to Approximate Them All: Amortized Variational Inference of Ising Ground States
Sebastian Sanokowski ⋅ Wilhelm Berghammer ⋅ Johannes Kofler ⋅ Sepp Hochreiter ⋅ Sebastian Lehner
Hybrid integration of the gravitational N-body problem with Artificial Neural Networks
Veronica Saz Ulibarrena ⋅ Simon Portegies Zwart ⋅ Elena Sellentin ⋅ Barry Koren ⋅ Philipp Horn ⋅ Maxwell X. Cai
CAPE: Channel-Attention-Based PDE Parameter Embeddings for SciML
Makoto Takamoto ⋅ Francesco Alesiani ⋅ Mathias Niepert
Real-time Health Monitoring of Heat Exchangers using Hypernetworks and PINNs
Ritam Majumdar ⋅ Vishal Jadhav ⋅ Anirudh Deodhar ⋅ Shirish Karande ⋅ Lovekesh Vig ⋅ Venkataramana Runkana
Neural Inference of Gaussian Processes for Time Series Data of Quasars
Egor Danilov ⋅ Aleksandra Ciprijanovic ⋅ Brian Nord
Deep Learning-Based Spatiotemporal Multi-Event Reconstruction for Delay-Line Detectors
Marco Knipfer ⋅ Sergei Gleyzer ⋅ Stefan Meier ⋅ Jonas Heimerl ⋅ Peter Hommelhoff
Tensor networks for active inference with discrete observation spaces
Samuel T. Wauthier ⋅ Bram Vanhecke ⋅ Tim Verbelen ⋅ Bart Dhoedt
Employing CycleGANs to Generate Realistic STEM Images for Machine Learning
Abid Khan ⋅ Chia-Hao Lee ⋅ Pinshane Y. Huang ⋅ Bryan Clark
HubbardNet: Efficient Predictions of the Bose-Hubbard Model Spectrum with Deep Neural Networks
Ziyan Zhu ⋅ Marios Mattheakis ⋅ Weiwei Pan ⋅ Efthimios Kaxiras
Strong-Lensing Source Reconstruction with Denoising Diffusion Restoration Models
Konstantin Karchev ⋅ Noemi Anau Montel ⋅ Adam Coogan ⋅ Christoph Weniger
Score-based Seismic Inverse Problems
Sriram Ravula ⋅ Dimitri Voytan ⋅ Elad Liebman ⋅ Ram Tuvi ⋅ Yash Gandhi ⋅ Hamza Ghani ⋅ Alex Ardel ⋅ Mrinal Sen ⋅ Alex Dimakis
Deep-pretrained-FWI: combining supervised learning with physics-informed neural network
ANA PAULA MULLER ⋅ Clecio Roque Bom ⋅ Jessé Carvalho Costa ⋅ Elisângela Lopes Faria ⋅ Marcelo Portes de Albuquerque ⋅ Marcio Portes de Albuquerque
Differentiable composition for model discovery
Omer Rochman Sharabi ⋅ Gilles Louppe
Improving Generalization with Physical Equations
Antoine Wehenkel ⋅ Jens Behrmann ⋅ Hsiang Hsu ⋅ Guillermo Sapiro ⋅ Gilles Louppe ⋅ Joern-Henrik Jacobsen
Neural Fields for Fast and Scalable Interpolation of Geophysical Ocean Variables
Juan Emmanuel Johnson ⋅ Redouane Lguensat ⋅ ronan fablet ⋅ Emmanuel Cosme ⋅ Julien Le Sommer
Interpretable Encoding of Galaxy Spectra
Yan Liang ⋅ Peter Melchior ⋅ Sicong Lu
Neural Network Prior Mean for Particle Accelerator Injector Tuning
Connie Xu ⋅ Ryan Roussel ⋅ Auralee Edelen
A robust estimator of mutual information for deep learning interpretability
Davide Piras ⋅ Hiranya Peiris ⋅ Andrew Pontzen ⋅ Luisa Lucie-Smith ⋅ Brian Nord ⋅ Ningyuan (Lillian) Guo
DIGS: Deep Inference of Galaxy Spectra with Neural Posterior Estimation
Gourav Khullar ⋅ Brian Nord ⋅ Aleksandra Ciprijanovic ⋅ Jason Poh ⋅ Fei Xu ⋅ Ashwin Samudre
Strong Lensing Parameter Estimation on Ground-Based Imaging Data Using Simulation-Based Inference
Jason Poh ⋅ Ashwin Samudre ⋅ Aleksandra Ciprijanovic ⋅ Brian Nord ⋅ Joshua Frieman ⋅ Gourav Khullar
Closing the resolution gap in Lyman alpha simulations with deep learning
Cooper Jacobus ⋅ Peter Harrington ⋅ Zarija Lukić
Do graph neural networks learn jet substructure?
Farouk Mokhtar ⋅ Raghav Kansal ⋅ Javier Duarte
Thermophysical Change Detection on the Moon with the Lunar Reconnaissance Orbiter Diviner sensor
Jose Delgado-Centeno ⋅ Silvia Bucci ⋅ Ziyi Liang ⋅ Ben Gaffinet ⋅ Valentin T. Bickel ⋅ Ben Moseley ⋅ Miguel Olivares
Geometry-aware Autoregressive Models for Calorimeter Shower Simulations
Junze Liu ⋅ Aishik Ghosh ⋅ Dylan Smith ⋅ Pierre Baldi ⋅ Daniel Whiteson
Statistical Inference for Coadded Astronomical Images
Mallory Wang ⋅ Ismael Mendoza ⋅ Jeffrey Regier ⋅ Camille Avestruz ⋅ Cheng Wang
Domain Adaptation for Simulation-Based Dark Matter Searches with Strong Gravitational Lensing
Pranath Reddy Kumbam ⋅ Sergei Gleyzer ⋅ Michael Toomey ⋅ Marcos Tidball
Data-driven discovery of non-Newtonian astronomy via learning non-Euclidean Hamiltonian
Oswin So ⋅ Gongjie Li ⋅ Evangelos Theodorou ⋅ Molei Tao
Deconvolving Detector Effects for Distribution Moments
Krish Desai ⋅ Benjamin Nachman ⋅ Jesse Thaler
Multi-scale Digital Twin: Developing a fast and physics-infused surrogate model for groundwater contamination with uncertain climate models
Lijing Wang ⋅ Takuya Kurihana ⋅ Aurelien Meray ⋅ Ilijana Mastilovic ⋅ Satyarth Praveen ⋅ Zexuan Xu ⋅ Milad Memarzadeh ⋅ Alexander Lavin ⋅ Haruko Wainwright
Topological Jet Tagging
Dawson Thomas ⋅ Sarah Demers ⋅ Smita Krishnaswamy ⋅ Bastian Rieck
Physics-Driven Convolutional Autoencoder Approach for CFD Data Compressions
Alberto Olmo ⋅ Ahmed Zamzam ⋅ Andrew Glaws ⋅ Ryan King
Recovering Galaxy Cluster Convergence from Lensed CMB with Generative Adversarial Networks
Liam Parker ⋅ Dongwon Han ⋅ Shirley Ho ⋅ Pablo Lemos
DiffDock: Diffusion Steps, Twists, and Turns for Molecular Docking
Gabriele Corso ⋅ Hannes Stärk ⋅ Bowen Jing ⋅ Regina Barzilay ⋅ Tommi Jaakkola
Normalizing Flows for Fragmentation and Hadronization
Ahmed Youssef ⋅ Philip Ilten ⋅ Tony Menzo ⋅ Jure Zupan ⋅ Manuel Szewc ⋅ Stephen Mrenna ⋅ Michael K. Wilkinson
Astronomical Image Coaddition with Bundle-Adjusting Radiance Fields
Harlan Hutton ⋅ Harshitha Palegar ⋅ Shirley Ho ⋅ Miles Cranmer ⋅ Peter Melchior ⋅ Jenna Eubank
Differentiable Physics-based Greenhouse Simulation
Nhat M. Nguyen ⋅ Hieu Tran ⋅ Minh Duong ⋅ Hanh Bui ⋅ Kenneth Tran
GAN-Flow: A dimension-reduced variational framework for physics-based inverse problems
Agnimitra Dasgupta ⋅ Dhruv Patel ⋅ Deep Ray ⋅ Erik Johnson ⋅ Assad Oberai
Control and Calibration of GlueX Central Drift Chamber Using Gaussian Process Regression
Diana McSpadden ⋅ Torri Jeske ⋅ Naomi Jarvis ⋅ David Lawrence ⋅ Thomas Britton ⋅ nikhil kalra
Emulating cosmological growth functions with B-Splines
Ngai Pok Kwan ⋅ Chirag Modi ⋅ Yin Li ⋅ Shirley Ho
ClimFormer - a Spherical Transformer model for long-term climate projections
Salva Rühling Cachay ⋅ Peetak Mitra ⋅ Sookyung Kim ⋅ Subhashis Hazarika ⋅ Haruki Hirasawa ⋅ Dipti Hingmire ⋅ Hansi Singh ⋅ Kalai Ramea
Computing the Bayes-optimal classifier and exact maximum likelihood estimator with a semi-realistic generative model for jet physics
Kyle Cranmer ⋅ Matthew Drnevich ⋅ Lauren Greenspan ⋅ Sebastian Macaluso ⋅ Duccio Pappadopulo
The Senseiver: attention-based global field reconstruction from sparse observations
Javier E. Santos ⋅ Zachary Fox ⋅ Arvind Mohan ⋅ Hari Viswanathan ⋅ NIcholas Lubbers
Skip Connections for High Precision Regressors
Ayan Paul ⋅ Fady Bishara ⋅ Jennifer Dy
Likelihood-Free Frequentist Inference for Calorimetric Muon Energy Measurement in High-Energy Physics
Luca Masserano ⋅ Ann Lee ⋅ Rafael Izbicki ⋅ Mikael Kuusela ⋅ tommaso dorigo
Uncertainty Aware Deep Learning for Particle Accelerators
Kishansingh Rajput ⋅ Malachi Schram ⋅ Karthik Somayaji NS
Graphical Models are All You Need: Per-interaction reconstruction uncertainties in a dark matter detection experiment
Christina Peters ⋅ Aaron Higuera ⋅ Shixiao Liang ⋅ Waheed Bajwa ⋅ Christopher Tunnell
PELICAN: Permutation Equivariant and Lorentz Invariant or Covariant Aggregator Network for Particle Physics
Jan Offermann ⋅ Alexander Bogatskiy ⋅ Timothy Hoffman ⋅ David W Miller
FO-PINNs: A First-Order formulation for Physics~Informed Neural Networks
Rini Jasmine Gladstone ⋅ Mohammad Amin Nabian ⋅ Hadi Meidani
Geometric NeuralPDE (GNPnet) Models for Learning Dynamics
Oluwadamilola Fasina ⋅ Smita Krishnaswamy ⋅ Aditi Krishnapriyan
PIPS: Path Integral Stochastic Optimal Control for Path Sampling in Molecular Dynamics
Lars Holdijk ⋅ Yuanqi Du ⋅ Ferry Hooft ⋅ Priyank Jaini ⋅ Berend Ensing ⋅ Max Welling
Predicting Full-Field Turbulent Flows Using Fourier Neural Operator
Peter Renn ⋅ Sahin Lale ⋅ Cong Wang ⋅ Zongyi Li ⋅ Anima Anandkumar ⋅ Morteza Gharib
A Self-Supervised Approach to Reconstruction in Sparse X-Ray Computed Tomography
Rey Mendoza ⋅ Minh Nguyen ⋅ Judith Weng Zhu ⋅ Talita Perciano ⋅ Vincent Dumont ⋅ Juliane Mueller ⋅ Vidya Ganapati
Energy based models for tomography of quantum spin-lattice systems
Abhijith Jayakumar ⋅ Marc Vuffray ⋅ Andrey Lokhov
Towards a non-Gaussian Generative Model of large-scale Reionization Maps
Yu-Heng Lin ⋅ Sultan Hassan ⋅ Bruno Régaldo-Saint Blancard ⋅ Michael Eickenberg ⋅ Chirag Modi
Adversarial Noise Injection for Learned Turbulence Simulations
Jingtong Su ⋅ Julia Kempe ⋅ Drummond Fielding ⋅ Nikolaos Tsilivis ⋅ Miles Cranmer ⋅ Shirley Ho
Shining light on data
Akshat Kumar ⋅ Mohan Sarovar
A Novel Automatic Mixed Precision Approach For Physics Informed Training
Jinze Xue ⋅ Akshay Subramaniam ⋅ Mark Hoemmen
Atmospheric retrievals of exoplanets using learned parameterizations of pressure-temperature profiles
Timothy Gebhard ⋅ Daniel Angerhausen ⋅ Björn Konrad ⋅ Eleonora Alei ⋅ Sascha Quanz ⋅ Bernhard Schölkopf
Posterior samples of source galaxies in strong gravitational lenses with score-based priors
Alexandre Adam ⋅ Adam Coogan ⋅ Nikolay Malkin ⋅ Ronan Legin ⋅ Laurence Perreault-Levasseur ⋅ Yashar Hezaveh ⋅ Yoshua Bengio
Particle-level Compression for New Physics Searches
Yifeng Huang ⋅ Jack Collins ⋅ Benjamin Nachman ⋅ Simon Knapen ⋅ Daniel Whiteson
CaloMan: Fast generation of calorimeter showers with density estimation on learned manifolds
Jesse Cresswell ⋅ Brendan Ross ⋅ Gabriel Loaiza-Ganem ⋅ Humberto Reyes-Gonzalez ⋅ Marco Letizia ⋅ Anthony Caterini
Learning Integrable Dynamics with Action-Angle Networks
Ameya Daigavane ⋅ Arthur Kosmala ⋅ Miles Cranmer ⋅ Tess Smidt ⋅ Shirley Ho
One-Class Dense Networks for Anomaly Detection
Norman Karr ⋅ Benjamin Nachman ⋅ David Shih
Emulating cosmological multifields with generative adversarial networks
Sambatra Andrianomena ⋅ Sultan Hassan ⋅ Francisco Villaescusa-Navarro
Monte Carlo Techniques for Addressing Large Errors and Missing Data in Simulation-based Inference
Bingjie Wang ⋅ Joel Leja ⋅ Victoria Villar ⋅ Joshua Speagle
Towards Creating Benchmark Datasets of Universal Neural Network Potential for Material Discovery
So Takamoto ⋅ Chikashi Shinagawa ⋅ Nontawat Charoenphakdee
Physics-informed neural networks for modeling rate- and temperature-dependent plasticity
Rajat Arora ⋅ Pratik Kakkar ⋅ Amit Chakraborty ⋅ Biswadip Dey
A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithful
Joeri Hermans ⋅ Arnaud Delaunoy ⋅ François Rozet ⋅ Antoine Wehenkel ⋅ Volodimir Begy ⋅ Gilles Louppe
Learning-based solutions to nonlinear hyperbolic PDEs: Empirical insights on generalization errors
Bilal Thonnam Thodi ⋅ Sai Venkata Ramana Ambadipudi ⋅ Saif Eddin Jabari
Improved Training of Physics-informed Neural Networks using Energy-Based priors: A Study on Electrical Impedance Tomography
Akarsh Pokkunuru ⋅ Pedram Rooshenas ⋅ Thilo Strauss ⋅ Anuj Abhishek ⋅ Taufiquar Khan
How good is the Standard Model? Machine learning multivariate Goodness of Fit tests
Gaia Grosso ⋅ Marco Letizia ⋅ Andrea Wulzer ⋅ Maurizio Pierini
A probabilistic deep learning model to distinguish cusps and cores in dwarf galaxies
Julen Expósito Márquez ⋅ Marc Huertas-Company ⋅ Arianna Di Cintio ⋅ Chris Brook ⋅ Andrea Macciò ⋅ Rob Grant ⋅ Elena Arjona
Using Shadows to Learn Ground State Properties of Quantum Hamiltonians
Viet T. Tran ⋅ Laura Lewis ⋅ Johannes Kofler ⋅ Hsin-Yuan Huang ⋅ Richard Kueng ⋅ Sepp Hochreiter ⋅ Sebastian Lehner
Set-Conditional Set Generation for Particle Physics
Sanmay Ganguly ⋅ Lukas Heinrich ⋅ Nilotpal Kakati ⋅ Nathalie Soybelman
Score Matching via Differentiable Physics
Benjamin Holzschuh ⋅ Simona Vegetti ⋅ Nils Thuerey
Adaptive Selection of Atomic Fingerprints for High-Dimensional Neural Network Potentials
Johannes Sandberg ⋅ Emilie Devijver ⋅ Noel Jakse ⋅ Thomas Voigtmann
HyperFNO: Improving the Generalization Behavior of Fourier Neural Operators
Francesco Alesiani ⋅ Makoto Takamoto ⋅ Mathias Niepert
Normalizing Flows for Hierarchical Bayesian Analysis: A Gravitational Wave Population Study
David Ruhe ⋅ Kaze Wong ⋅ Miles Cranmer ⋅ Patrick Forré
Fast kinematics modeling for conjunction with lens image modeling
Matthew Gomer ⋅ Luca Biggio ⋅ Sebastian Ertl ⋅ Han Wang ⋅ Aymeric Galan ⋅ Lyne Van de Vyvere ⋅ Dominique Sluse ⋅ Georgios Vernardos ⋅ Sherry Suyu
Multi-Fidelity Transfer Learning for accurate database PDE approximation
Wenzhuo LIU ⋅ Mouadh Yagoubi ⋅ Marc Schoenauer ⋅ David Danan
Learning Electron Bunch Distribution along a FEL Beamline by Normalising Flows
Anna Willmann ⋅ Jurjen Pieter Couperus Cabadağ ⋅ Yen-Yu Chang ⋅ Richard Pausch ⋅ Amin Ghaith ⋅ Alexander Debus ⋅ Arie Irman ⋅ Michael Bussmann ⋅ Ulrich Schramm ⋅ Nico Hoffmann
Continual learning autoencoder training for a particle-in-cell simulation via streaming
Patrick Stiller ⋅ Varun Makdani ⋅ Franz Poeschel ⋅ Richard Pausch ⋅ Alexander Debus ⋅ Michael Bussmann ⋅ Nico Hoffmann
On Using Deep Learning Proxies as Forward Models in Optimization Problems
Fatima Albreiki ⋅ Nidhal Belayouni ⋅ Deepak Gupta
HGPflow: Particle reconstruction as hyperedge prediction
Etienne Dreyer ⋅ Nilotpal Kakati ⋅ Francesco Armando Di Bello
Anomaly Detection with Multiple Reference Datasets in High Energy Physics
Mayee Chen ⋅ Benjamin Nachman ⋅ Frederic Sala
Do Better QM9 Models Extrapolate as Better Quantum Chemical Property Predictors?
YUCHENG ZHANG ⋅ Nontawat Charoenphakdee ⋅ So Takamoto
Diversity Balancing Generative Adversarial Networks for fast simulation of the Zero Degree Calorimeter in the ALICE experiment at CERN
Jan Dubiński ⋅ Kamil Deja ⋅ Sandro Wenzel ⋅ Przemysław Rokita ⋅ Tomasz Trzcinski
Identifying Hamiltonian Manifold in Neural Networks
Yeongwoo Song ⋅ Hawoong Jeong
Physics-Informed Neural Networks as Solvers for the Time-Dependent Schrödinger Equation
Karan Shah ⋅ Patrick Stiller ⋅ Nico Hoffmann ⋅ Attila Cangi
Time-aware Bayesian optimization for adaptive particle accelerator tuning
Nikita Kuklev ⋅ Yine Sun ⋅ Hairong Shang ⋅ Michael Borland ⋅ Gregory Fystro
Inferring molecular complexity from mass spectrometry data using machine learning
Timothy Gebhard ⋅ Aaron C. Bell ⋅ Jian Gong ⋅ Jaden J. A. Hastings ⋅ George Fricke ⋅ Nathalie Cabrol ⋅ Scott Sandford ⋅ Michael Phillips ⋅ Kimberley Warren-Rhodes ⋅ Atilim Gunes Baydin
Towards solving model bias in cosmic shear forward modeling
Benjamin Remy ⋅ Francois Lanusse ⋅ Jean-Luc Starck
Physical Data Models in Machine Learning Imaging Pipelines
Marco Aversa ⋅ Luis Oala ⋅ Christoph Clausen ⋅ Roderick Murray-Smith ⋅ Bruno Sanguinetti
Amortized Bayesian Inference of GISAXS Data with Normalizing Flows
Maksim Zhdanov ⋅ Lisa Randolph ⋅ Thomas Kluge ⋅ Motoaki Nakatsutsumi ⋅ Christian Gutt ⋅ Marina Ganeva ⋅ Nico Hoffmann
Insight into cloud processes from unsupervised classification with a rotation-invariant autoencoder
Takuya Kurihana ⋅ James Franke ⋅ Ian Foster ⋅ Ziwei Wang ⋅ Elisabeth Moyer
Addressing out-of-distribution data for flow-based gravitational wave inference
Maximilian Dax ⋅ Stephen Green ⋅ Jonas Wildberger ⋅ Jonathan Gair ⋅ Michael Puerrer ⋅ Jakob Macke ⋅ Alessandra Buonanno ⋅ Bernhard Schölkopf
A fast and flexible machine learning approach to data quality monitoring
Marco Letizia ⋅ Gaia Grosso ⋅ Andrea Wulzer ⋅ Marco Zanetti ⋅ Jacopo Pazzini ⋅ Marco Rando ⋅ Nicolò Lai
Cosmology from Galaxy Redshift Surveys with PointNet
Sotiris Anagnostidis ⋅ Arne Thomsen ⋅ Alexandre Refregier ⋅ Tomasz Kacprzak ⋅ Luca Biggio ⋅ Thomas Hofmann ⋅ Tilman Tröster
Finding active galactic nuclei through Fink
Etienne Russeil ⋅ Emille Ishida ⋅ Julien Peloton ⋅ Anais Möller ⋅ Roman Le Montagner