Description
IDs Title Presenters
4 Analyzing ML-enabled Full Population Model for Galaxy SEDs with Unsupervised Learning and Mutual Information Sinan Deger
7 Quark/gluon discrimination and top tagging with dual attention transformer Daohan Wang
21 Learning the ‘Match’ Manifold to Accelerate Template Bank Generation Susanna Green
25 Optimal, fast, and robust inference of reionization-era cosmology with the 21cmPIE-INN Benedikt Schosser
40 Rapidly searching and producing Bayesian posteriors for neutron stars in gravitational wave data. Joe Bayley
41 Convolutional neural network search for long-duration transient gravitational waves from glitching pulsars Rodrigo Tenorio
44 GNN for Λ Hyperon Reconstruction in the WASA-FRS Experiment Snehankit Pattnaik
54 OmniJet: The first cross-task foundation model for particle physics Joschka Birk
55 Turning optimal classifiers into anomaly detectors Adrian Rubio Jimenez
58 Gradient-Annihilated PINNs for Solving Riemann Problems: Application to Relativistic Hydrodynamics Antonio Ferrer Sánchez
60 Increasing the model agnosticity of weakly supervised anomaly detection Marie Hein
67 Multi-class classification of gamma-ray sources and the nature of excess of GeV gamma rays near the Galactic center Dmitry Malyshev
69 Estimation of Machine Learning model uncertainty in particle physics event classifiers julia vazquez escobar
70 Robust Uncertainty Quantification in Parton Distribution Function Inference Mark Costantini
75 Symbolic regression for precision LHC physics Manuel Morales-Alvarado
78 Deep learning techniques in the study of the hypertriton puzzle Christophe Rappold
82 Next-Generation Source Analysis: AI Techniques for Data-Intensive Astronomical Observations Rodney Nicolaas Nicolaas
83 Flexible joint conditional normalizing flow distributions over manifolds: the jammy-flows toolkit Thorsten Glüsenkamp
85 Finetuning Foundation Models for Joint Analysis Optimization Lukas Heinrich
90 Calculating entanglement entropy with generative neural networks Dawid Zapolski
95 Energy-based graph autoencoders for semivisible jet tagging in the Lund representation Roberto Seidita
97 Fast and Precise Amplitude Surrogates with Bayesian and Symmetry Preserving Networks Víctor Bresó Pla
98 Galaxy redshift estimations with transfer and multi-task learning Martin Boerstad Eriksen
99 Quark/gluon tagging in CMS Open Data with CWoLa and TopicFlow Ayodele Ore
105 Generating Lagrangians for particle theories Eliel Camargo-Molina
106 Evaluating Generative Models with non-parametric two-sample tests Samuele Grossi
107 The flash-simulation of the LHCb experiment using the Lamarr framework Matteo Barbetti
110 Utilizing Artificial Intelligence Technologies for the Enhancement of X-ray Spectroscopy with Metallic-Magnetic Calorimeters Marc Oliver Herdrich
112 Applying hierarchical autoregressive neural networks for three-dimensional Ising model Mateusz Winiarski
117 End-to-End Object Reconstruction in a Sampling-Calorimeter using YOLO Pruthvi Suryadevara
118 Validating Explainable AI Techniques through High Energy Physics Data Mariagrazia Monteleone
126 Transformer-inspired models for particle track reconstruction Yue Zhao
127 Sensitivity of strong lenses to substructure with machine learning Conor O'Riordan
134 A fast convolutional neural network for online particle track recognition Viola Cavallini
139 A deep learning method for the gamma-ray identification with the DAMPE space mission Jennifer Maria Frieden
143 Flavour Tagging with Graph Neural Networks with the ATLAS experiment Walter Leinonen
145 A deep learning method for the trajectory reconstruction of gamma rays with the DAMPE space mission Parzival Nussbaum
146 Unsupervised tagging of semivisible jets with energy-based autoencoders in CMS Florian Eble
152 Precision-Machine Learning for the Matrix Element Method Theo Heimel
153 Unsupervised Classification of Radio Sources Through Self-Supervised Representation Learning Nicolas Baron Perez
163 Model selection with normalizing flows Rahul Srinivasan
164 Towards the first time ever measurement of the $gg\rightarrow ZH$ process at the LHC using Transformer networks Geoffrey Gilles
165 Next generation cosmological analysis with a re-usable library of machine learning emulators across a variety of cosmological models Dily Duan Yi Ong
172 LHC Event Generation with JetGPT Jonas Spinner
179 Machine-learning analysis of cosmic-ray nuclei data from the AMS-02 experiment Shahid Khan
182 b-hive: a modular training framework for state-of-the-art object-tagging within the python ecosystem at the CMS experiment Niclas Eich
183 FlashSim: an end-to-end fast simulation prototype using Normalizing Flow Francesco Vaselli
193 Improving Two-Neutron Detection Efficiency on the NEBULA Detector using XGBoost Algorithm Yutian Li
195 Reconstruction of Low Mass Vector Mesons via Dimuon decay channel using Machine Learning Technique for the CBM Experiment at FAIR Abhishek Kumar Sharma
201 Reconstructing the Neutron Star Equation of State with Bayesian deep learning Giulia Ventagli
202 A Neural-Network-defined Gaussian Mixture Model for particle identification in LHCb Edoardo Franzoso
204 Deep learning predicted elliptic flow of identified particles in heavy-ion collisions at the RHIC and LHC energies Gergely Gábor Barnaföldi
205 Anomaly detection search for BSM physics in ATLAS experiment at LHC Francesco Cirotto
208 Simulation Based Inference from the CD-EoR 21-cm signal Anchal Saxena
214 Deep support vector data description models on an analog in-memory computing platform for real-time unsupervised anomaly detection. Dominique Kosters
215 Application of science-informed AI in experimental particle physics and neuroscience Peter Levai
217 Tuning neural posterior estimation for gravitational wave inference Alex Kolmus
220 Using ML based Unfolding to reduce error on lattice QCD observables Simran Singh
221 Addressing Real-World Noise Challenges in Gravitational Wave Parameter Estimation with Truncated Marginal Neural Ratio Estimation Alexandra Wernersson
222 Fully Bayesian Forecasts with Neural Bayes Ratio Estimation Thomas Gessey-Jones
