Recent Publications¶
This is an automatically compiled list of papers which have been added to the living review that were made public within the previous 4 months at the time of updating. This is not an exhaustive list of released papers, and is only able to find those which have both year and month data provided in the bib reference.
August 2025¶
- Robust anomaly triggers with {\textbackslash}textsc{DecADe} (2025)
- Jet Image Tagging Using Deep Learning: An Ensemble Model (2025)
- Machine Learning Power Week 2023: Clustering in Hadronic Calorimeters (2025)
- Real-Time Analysis of Unstructured Data with Machine Learning on Heterogeneous Architectures (2025)
- Learning geometries beyond asymptotic AdS (2025)
- Investigating 1-Bit Quantization in Transformer-Based Top Tagging (2025)
- Approaching Maximal Information Extraction in Low-Signal Regimes via Multiple Instance Learning (2025)
- Rediscovering the Standard Model with AI (2025)
- Viability of perturbative expansion for quantum field theories on neurons (2025)
- Boosting Sensitivity to \(HH\to b\bar{b} γγ\) with Graph Neural Networks and XGBoost (2025)
- Exact CHY Integrand Construction Using Combinatorial Neural Networks and Discrete Optimization (2025)
- Jet Image Generation in High Energy Physics Using Diffusion Models (2025)
- Comparing Generative Models with the New Physics Learning Machine (2025)
- Symbolic regression and precision LHC physics (2025)
- Criticality analysis of nuclear binding energy neural networks (2025)
July 2025¶
- Search for \(t\bar tt\bar tW\) Production at $\sqrt{s} (2025)
- Simulation-based inference for Precision Neutrino Physics through Neural Monte Carlo tuning (2025)
- Variational Neural Network Approach to QFT in the Field Basis (2025)
- Fast prediction of the hydrodynamic QGP evolution in ultra-relativistic heavy-ion collisions using Fourier Neural Operators (2025)
- Anomaly detection with spiking neural networks for LHC physics (2025)
- How to Deep-Learn the Theory behind Quark-Gluon Tagging (2025)
- Neural network extraction of chromo-electric and chromo-magnetic gluon masses (2025)
- Towards a Large Physics Benchmark (2025)
- Reconstructing Sparticle masses at the LHC using Generative Machine Learning (2025)
- Deep Neural Network Driven Simulation Based Inference Method for Pole Position Estimation under Model Misspecification (2025)
- Decoding the proton's gluonic density with lattice QCD-informed machine learning (2025)
- On Focusing Statistical Power for Searches and Measurements in Particle Physics (2025)
- A linear PDF model for Bayesian inference (2025)
- Ring-based ML calibration with in situ pileup correction for real-time jet triggers (2025)
- Deep learning approaches to top FCNC couplings to photons at the LHC (2025)
- Simulation-Prior Independent Neural Unfolding Procedure (2025)
- Toward an event-level analysis of hadron structure using differential programming (2025)
- Analysis note: measurement of thrust in \(e^{+}e^{-}\) collisions at \(\sqrt{s}\) (2025)
- Theory-informed neural networks for particle physics (2025)
- Deep Image Reconstruction for Background Subtraction in Heavy-Ion Collisions (2025)
- FlexCAST: Enabling Flexible Scientific Data Analyses (2025)
- A Practical Guide to Unbinned Unfolding (2025)
- Noise Filtering Algorithm Based on Graph Neural Network for STCF Drift Chamber (2025)
- CycleGAN-Driven Transfer Learning for Electronics Response Emulation in High-Purity Germanium Detectors (2025)
- Mind the Gap: Navigating Inference with Optimal Transport Maps (2025)
- Search for a Dark Gauge Boson Within Einstein-Cartan Theory at the ILC Using Multivariate Analysis (2025)
- Learning Pole Structures of Hadronic States using Predictive Uncertainty Estimation (2025)
- High-Dimensional Unfolding in Large Backgrounds (2025)
- Data-Driven Einstein-Dilaton Model for Pure Yang-Mills Thermodynamics and Glueball Spectrum (2025)
- Reconstruction of cosmic-ray properties with GNN in GRAND (2025)
- \(\mathcal{CP}\)-Analyses with Symbolic Regression (2025)
- The Neural Networks with Tensor Weights and the Corresponding Fermionic Quantum Field Theory (2025)
- Online Electron Reconstruction at CLAS12 (2025)
- Replacing detector simulation with heterogeneous GNNs in flavour physics analyses (2025)
- Transforming Calabi-Yau Constructions: Generating New Calabi-Yau Manifolds with Transformers (2025)
- Neural Unfolding of the Chiral Magnetic Effect in Heavy-Ion Collisions (2025)
- Real-Time Graph-based Point Cloud Networks on FPGAs via Stall-Free Deep Pipelining (2025)
- Exploring potential of OpenAI o3 as a signal-agnostic model for Signal/Background separation in \(t \rightarrow uZ\) FCNC Searches at Future Hadron Colliders (2025)
- da4ml: Distributed Arithmetic for Real-time Neural Networks on FPGAs (2025)
- ML-based muon identification using a FNAL-NICADD scintillator chamber for the MID subsystem of ALICE 3 (2025)
- Deep Learning and Model Independence (2025)
- A Frequentist Simulation-Based Inference Treatment of Sterile Neutrino Global Fits (2025)
- Direct Vertex Reconstruction of \(\Lambda\) Baryons from Hits in CLAS12 using Graph Neural Networks (2025)
- Neural simulation-based inference of the Higgs trilinear self-coupling via off-shell Higgs production (2025)
June 2025¶
- Solving inverse problems of Type IIB flux vacua with conditional generative models (2025)
- CaloHadronic: a diffusion model for the generation of hadronic showers (2025)
- Discovering the underlying analytic structure within Standard Model constants using artificial intelligence (2025)
- Testing a 95 GeV Scalar at the CEPC with Machine Learning (2025)
- Graph theory inspired anomaly detection at the LHC (2025)
- DeepQuark: deep-neural-network approach to multiquark bound states (2025)
- Experimental Determination of BSM Triple Higgs Couplings at the HL-LHC with Neural Networks (2025)
- Solving the QCD effective kinetic theory with neural networks (2025)
- Unlocking Multi-Dimensional Integration with Quantum Adaptive Importance Sampling (2025)
- Neutrino Telescope Event Classification on Quantum Computers (2025)
- Approximate Ricci-flat Metrics for Calabi-Yau Manifolds (2025)
- Jet Reconstruction with Mamba Networks in Collider Events (2025)
- Efficient many-jet event generation with Flow Matching (2025)
- Performance of the FARICH-based particle identification at charm superfactories using machine learning (2025)
- Large Language Models -- the Future of Fundamental Physics? (2025)
- Review of Machine Learning for Real-Time Analysis at the Large Hadron Collider experiments ALICE, ATLAS, CMS and LHCb (2025)
- Proposed measurement of longitudinally polarised vector bosons in \(WH\) and \(ZH\) production at Hadron colliders (2025)
- Learning Before Filtering: Real-Time Hardware Learning at the Detector Level (2025)
- Improved Ground State Estimation in Quantum Field Theories via Normalising Flow-Assisted Neural Quantum States (2025)
- Machine Learning Left-Right Breaking from Gravitational Waves (2025)
- Machine Learning for the Cluster Reconstruction in the CALIFA Calorimeter at R3B (2025)
- Guided Graph Compression for Quantum Graph Neural Networks (2025)
- Towards AI-assisted Neutrino Flavor Theory Design (2025)
- Search for top squarks in final states with many light-flavor jets and 0, 1, or 2 charged leptons in proton-proton collisions at \(\sqrt{s}\) (2025)
- Machine learning method for enforcing variable independence in background estimation with LHC data: ABCDisCoTEC (2025)
- Data-Driven High-Dimensional Statistical Inference with Generative Models (2025)
- Application of quantum machine learning using variational quantum classifier in accelerator physics (2025)
- Accelerating multijet-merged event generation with neural network matrix element surrogates (2025)
- Hunting and identifying coloured resonances in four top events with machine learning (2025)
- Line shape analysis of \(\Lambda(1405)\) in \(\gamma p \rightarrow K^+\Sigma^-\pi^+\) reaction using convolutional neural network (2025)
- Bayesian network 3D event reconstruction in the Cygno optical TPC for dark matter direct detection (2025)
- Physics-Informed Neural Network Approach to Quark-Antiquark Color Flux Tube (2025)
- Physics and Computing Performance of the EggNet Tracking Pipeline (2025)
May 2025¶
- Tensor Network for Anomaly Detection in the Latent Space of Proton Collision Events at the LHC (2025)
- Generator Based Inference (GBI) (2025)
- A Start To End Machine Learning Approach To Maximize Scientific Throughput From The LCLS-II-HE (2025)
- Cluster Reconstruction in Electromagnetic Calorimeters Using Machine Learning Methods (2025)
- Frequentist Uncertainties on Neural Density Ratios with wifi Ensembles (2025)
- Hybrid-Graph Neural Network Method for Muon Fast Reconstruction in Neutrino Telescopes (2025)
- Transforming jet flavour tagging at ATLAS (2025)
- Search for \(CP\) violation in events with top quarks and Z bosons at \(\sqrt{s}\) (2025)
- What exactly did the Transformer learn from our physics data? (2025)
- Lorentz Local Canonicalization: How to Make Any Network Lorentz-Equivariant (2025)
- Real-time calibrations for future detectors at FAIR (2025)
- Comment on ''An implementation of neural simulation-based inference for parameter estimation in ATLAS'' (2025)
- Machine Learning the 6d Supergravity Landscape (2025)
- Particle identification in the GlueX detector using a multi-layer perceptron (2025)
- Fast Low Energy Reconstruction using Convolutional Neural Networks (2025)
- Sensitivity to New Physics Phenomena in Anomaly Detection: A Study of Untunable Hyperparameters (2025)
- A continuous calibration of the ATLAS flavour-tagging classifiers via optimal transportation maps (2025)
- Sampling NNLO QCD phase space with normalizing flows (2025)
- Unearthing large pseudoscalar Yukawa couplings with Machine Learning [DOI] (2025)
- Towards Foundation Models for Experimental Readout Systems Combining Discrete and Continuous Data (2025)
- Tagging fully hadronic exotic decays of the vectorlike \(\mathbf{B}\) quark using a graph neural network [DOI] (2025)
- Training neural control variates using correlated configurations (2025)
- Contrastive Normalizing Flows for Uncertainty-Aware Parameter Estimation (2025)
- Deep Neural Networks for Cross-Energy Particle Identification at RHIC and LHC (2025)
- Synthetic Training and Representation Bridging in Reconstruction Domains (2025)
- Unbinned inclusive cross-section measurements with machine-learned systematic uncertainties (2025)
- Design and FPGA Implementation of WOMBAT: A Deep Neural Network Level-1 Trigger System for Jet Substructure Identification and Boosted \(H\rightarrow b\bar{b}\) Tagging at the CMS Experiment (2025)
- Deep Learning to Improve the Sensitivity of Higgs Pair Searches in the \(4b\) Channel at the LHC (2025)
- Stay Positive: Neural Refinement of Sample Weights (2025)
- IAFormer: Interaction-Aware Transformer network for collider data analysis (2025)
- Search for new physics in final states with semi-visible jets or anomalous signatures using the ATLAS detector [DOI] (2025)
- Fast and Precise Track Fitting with Machine Learning (2025)