Copertina

Towards foundation-style models for energy-frontier heterogeneous neutrino detectors via self-supervised pre-training

Fuente: arXiv

Salvato in:

Dettagli Bibliografici
Autori principali:	Alonso-Monsalve, Saúl, Cufino, Fabio, Kose, Umut, Mascellani, Anna, Rubbia, André
Natura:	Preprint
Pubblicazione:	2026
Soggetti:	High Energy Physics - Experiment Computer Vision and Pattern Recognition
Accesso online:	Acceder al recurso
Tags:	Aggiungi Tag Nessun Tag, puoi essere il primo ad aggiungerne!!

Documenti analoghi

Deep-learning-based decomposition of overlapping-sparse images: application at the vertex of neutrino interactions
di: Alonso-Monsalve, Saúl, et al.
Pubblicazione: (2023)

Advances in Additive Manufacturing of 3D-segmented Plastic Scintillator Detectors for Particle Tracking and Calorimetry
di: Kose, Umut
Pubblicazione: (2024)

A 3D segmented Water-based Liquid Scintillator for high-precision detection of neutrinos in water
di: Li, Botao, et al.
Pubblicazione: (2025)

Masked self‐supervised pre‐training model for EEG‐based emotion recognition
di: Xinrong Hu, et al.
Pubblicazione: (2024)

Enhancing next token prediction based pre-training for jet foundation models
di: Birk, Joschka, et al.
Pubblicazione: (2025)

Reflexiones sobre el tema de la responsabilidad penal juvenil
di: Ennio Cufino
Pubblicazione: (2004)

Improving conversion rate prediction via self-supervised pre-training in online advertising
di: Shtoff, Alex, et al.
Pubblicazione: (2024)

Scaling up self-supervised learning for improved surgical foundation models
di: Jaspers, Tim J. M., et al.
Pubblicazione: (2025)

Transformer-Based Pulse Shape Discrimination in HPGe Detectors with Masked Autoencoder Pre-training
di: Babicz, Marta, et al.
Pubblicazione: (2026)

New avenues for the neutrino dipole portal exploration at the energy frontier
di: Vignaroli, Natascia
Pubblicazione: (2025)

Transferring self-supervised pre-trained models for SHM data anomaly detection with scarce labeled data
di: Zhou, Mingyuan, et al.
Pubblicazione: (2024)

El populismo de Fernando Vallejo
di: Oswaldo Ortegón Cufiño
Pubblicazione: (2016)

¡Deje hablar! La transferencia en “Las desdichas de Cardenio” de Don Quijote de la Mancha
di: Oswaldo Ortegón Cufiño
Pubblicazione: (2011)

Radio Galaxy Zoo: Morphological classification by Fanaroff-Riley designation using self-supervised pre-training
di: Buatthaisong, Nutthawara, et al.
Pubblicazione: (2025)

Compliant Non-Prehensile Pushing Manipulation
di: Cufino, Francesco, et al.
Pubblicazione: (2026)

Vascular anatomy-aware self-supervised pre-training for X-ray angiogram analysis
di: Huang, De-Xing, et al.
Pubblicazione: (2026)

Acoustic-to-articulatory inversion for dysarthric speech: Are pre-trained self-supervised representations favorable?
di: Maharana, Sarthak Kumar, et al.
Pubblicazione: (2023)

Systematic review of self-supervised foundation models for brain network representation using electroencephalography
di: Portmann, Hannah, et al.
Pubblicazione: (2026)

Thyroid ultrasound diagnosis improvement via multi-view self-supervised learning and two-stage pre-training
di: Wang, Jian, et al.
Pubblicazione: (2024)

What do self-supervised speech models know about Dutch? Analyzing advantages of language-specific pre-training
di: Kloots, Marianne de Heer, et al.
Pubblicazione: (2025)

Additive manufacturing of a 3D-segmented plastic scintillator detector for tracking and calorimetry of elementary particles
di: Weber, Tim, et al.
Pubblicazione: (2023)

DA-SSL: self-supervised domain adaptor to leverage foundational models in turbt histopathology slides
di: Zhang, Haoyue, et al.
Pubblicazione: (2025)

WV-Net: A foundation model for SAR WV-mode satellite imagery trained using contrastive self-supervised learning on 10 million images
di: Glaser, Yannik, et al.
Pubblicazione: (2024)

Data movement limits to frontier model training
di: Erdil, Ege, et al.
Pubblicazione: (2024)

The rising costs of training frontier AI models
di: Cottier, Ben, et al.
Pubblicazione: (2024)

Beam test results of a fully 3D-printed plastic scintillator particle detector prototype
di: Li, Botao, et al.
Pubblicazione: (2024)

Semi-visible jets, energy-based models, and self-supervision
di: Favaro, Luigi, et al.
Pubblicazione: (2023)

SS-DPPN: A self-supervised dual-path foundation model for the generalizable cardiac audio representation
di: Muna, Ummy Maria, et al.
Pubblicazione: (2025)

General surgery vision transformer: A video pre-trained foundation model for general surgery
di: Schmidgall, Samuel, et al.
Pubblicazione: (2024)

Contrastive Learning for Robust Representations of Neutrino Data
di: Wilkinson, Alex, et al.
Pubblicazione: (2025)

On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education
di: Wendlinger, Lorenz, et al.
Pubblicazione: (2024)

Single-channel electroencephalography decomposition by detector-atom network and its pre-trained model
di: Higashi, Hiroshi
Pubblicazione: (2024)

Tissue Concepts: supervised foundation models in computational pathology
di: Nicke, Till, et al.
Pubblicazione: (2024)

Revisiting semi-supervised learning in the era of foundation models
di: Zhang, Ping, et al.
Pubblicazione: (2025)

Paving the way for scientific foundation models: enhancing generalization and robustness in PDEs with constraint-aware pre-training
di: Totounferoush, Amin, et al.
Pubblicazione: (2025)

Two-detector flavor sensitivity to ultra-high-energy cosmic neutrinos
di: Testagrossa, Federico, et al.
Pubblicazione: (2023)

Light-weighted foundation model for seismic data processing based on representative and non-redundant pre-training dataset
di: Dong, Xintong, et al.
Pubblicazione: (2025)

Thermal neutrino self-energy beyond the contact approximation
di: Erdas, Andrea
Pubblicazione: (2023)

Enhanced active-sterile neutrino polarizability at the intensity frontier
di: Gehrlein, Julia, et al.
Pubblicazione: (2025)

Referential communication in heterogeneous communities of pre-trained visual deep networks
di: Mahaut, Matéo, et al.
Pubblicazione: (2023)