Copertina

Surrogate Neural Architecture Codesign Package (SNAC-Pack)

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Weitz, Jason, Demler, Dmitri, Hawks, Benjamin, Tran, Nhan, Duarte, Javier
Natura:	Preprint
Pubblicazione:	2025
Soggetti:	Machine Learning Artificial Intelligence High Energy Physics - Experiment
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Surrogate Neural Architecture Codesign Package (SNAC-Pack)
di: Weitz, Jason, et al.
Pubblicazione: (2026)

Neural Architecture Codesign for Fast Physics Applications
di: Weitz, Jason, et al.
Pubblicazione: (2025)

Uncertainty Quantification From Scaling Laws in Deep Neural Networks
di: Elsharkawy, Ibrahim, et al.
Pubblicazione: (2025)

High-dimensional and Permutation Invariant Anomaly Detection
di: Mikuni, Vinicius, et al.
Pubblicazione: (2023)

Guided Graph Compression for Quantum Graph Neural Networks
di: Casals, Mikel, et al.
Pubblicazione: (2025)

Spatially Aware Linear Transformer (SAL-T) for Particle Jet Tagging
di: Wang, Aaron, et al.
Pubblicazione: (2025)

Collider-Bench: Benchmarking AI Agents with Particle Physics Analysis Reproduction
di: Faroughy, Darius A., et al.
Pubblicazione: (2026)

Learning Pole Structures of Hadronic States using Predictive Uncertainty Estimation
di: Frohnert, Felix, et al.
Pubblicazione: (2025)

Improving Neutrino Oscillation Measurements through Event Classification
di: Ellis, Sebastian A. R., et al.
Pubblicazione: (2025)

Full Event Particle-Level Unfolding with Variable-Length Latent Variational Diffusion
di: Shmakov, Alexander, et al.
Pubblicazione: (2024)

Knowledge is Overrated: A zero-knowledge machine learning and cryptographic hashing-based framework for verifiable, low latency inference at the LHC
di: Jawahar, Pratik, et al.
Pubblicazione: (2025)

Training toward significance with the decorrelated event classifier transformer neural network
di: Kim, Jaebak
Pubblicazione: (2023)

AI Agents Can Already Autonomously Perform Experimental High Energy Physics
di: Moreno, Eric A., et al.
Pubblicazione: (2026)

MEDIC: a network for monitoring data quality in collider experiments
di: Bassa, Juvenal, et al.
Pubblicazione: (2025)

Differentiable Earth Mover's Distance for Data Compression at the High-Luminosity LHC
di: Shenoy, Rohan, et al.
Pubblicazione: (2023)

wa-hls4ml: A Benchmark and Surrogate Models for hls4ml Resource and Latency Estimation
di: Hawks, Benjamin, et al.
Pubblicazione: (2025)

Novel machine learning applications at the LHC
di: Duarte, Javier M.
Pubblicazione: (2024)

Deep Generative Models for Ultra-High Granularity Particle Physics Detector Simulation: A Voyage From Emulation to Extrapolation
di: Hashemi, Baran
Pubblicazione: (2024)

Neural posterior estimation of the neutrino direction in IceCube using transformer-encoded normalizing flows on the sphere
di: Abbasi, R., et al.
Pubblicazione: (2026)

Versor: A Geometric Sequence Architecture
di: Huy, Truong Minh, et al.
Pubblicazione: (2026)

Large Language Models for Physics Instrument Design
di: Zoccheddu, Sara, et al.
Pubblicazione: (2026)

Generative Models for Fast Simulation of Cherenkov Detectors at the Electron-Ion Collider
di: Giroux, James, et al.
Pubblicazione: (2025)

Learning Symmetry-Independent Jet Representations via Jet-Based Joint Embedding Predictive Architecture
di: Katel, Subash, et al.
Pubblicazione: (2024)

Robust Anomaly Detection for Particle Physics Using Multi-Background Representation Learning
di: Gandrakota, Abhijith, et al.
Pubblicazione: (2024)

Locality-Sensitive Hashing-Based Efficient Point Transformer with Applications in High-Energy Physics
di: Miao, Siqi, et al.
Pubblicazione: (2024)

Patch Hierarchical Attention Transformer for Efficient Particle Jet Tagging
di: Wang, Aaron, et al.
Pubblicazione: (2026)

Approximate Gaussianity Beyond Initialisation in Neural Networks
di: Hirst, Edward, et al.
Pubblicazione: (2025)

Improving robustness of jet tagging algorithms with adversarial training: exploring the loss surface
di: Stein, Annika
Pubblicazione: (2023)

Foundation models for high-energy physics
di: Hallin, Anna
Pubblicazione: (2025)

Agents of Discovery
di: Diefenbacher, Sascha, et al.
Pubblicazione: (2025)

Jet Image Tagging Using Deep Learning: An Ensemble Model
di: Bassa, Juvenal, et al.
Pubblicazione: (2025)

Towards a Self-Driving Trigger at the LHC: Adaptive Response in Real Time
di: Emami, Shaghayegh, et al.
Pubblicazione: (2026)

FM4NPP: A Scaling Foundation Model for Nuclear and Particle Physics
di: Park, David, et al.
Pubblicazione: (2025)

Comparative Study of Neural Network Methods for Solving Topological Solitons
di: Hashimoto, Koji, et al.
Pubblicazione: (2024)

AdS-GNN -- a Conformally Equivariant Graph Neural Network
di: Zhdanov, Maksim, et al.
Pubblicazione: (2025)

RINO: Renormalization Group Invariance with No Labels
di: Hao, Zichun, et al.
Pubblicazione: (2025)

Unification of Symmetries Inside Neural Networks: Transformer, Feedforward and Neural ODE
di: Hashimoto, Koji, et al.
Pubblicazione: (2024)

Discriminative versus Generative Approaches to Simulation-based Inference
di: Sluijter, Benjamin, et al.
Pubblicazione: (2025)

Probing SMEFT Operators through $t\bar{t}t\bar{t}$ Production with Hyper-Graph Neural Networks at the LHC
di: Subba, Amir, et al.
Pubblicazione: (2026)

An End-to-end Architecture for Collider Physics and Beyond
di: Qiu, Shi, et al.
Pubblicazione: (2026)