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In this work, we significantly enhance masked particle modeling (MPM), a self-supervised learning scheme for constructing highly expressive representations of unordered sets relevant to developing foundation models for high-energy physics.
Comparing partitions
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GEANT4: A Simulation toolkit
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Extracting and composing robust features with denoising autoencoders
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A brief introduction to pythia 8.1
Torbjörn Sjöstrand, Stephen Mrenna, and Peter Skands · 2008
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The anti-kt jet clustering algorithm
Matteo Cacciari, Gavin P Salam, and Gregory Soyez · 2008
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The CMS experiment at the CERN LHC
CMS Collaboration · 2008
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The ATLAS Experiment at the CERN Large Hadron Collider
ATLAS Collaboration · 2008
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Stacked denoising autoencoders: Learning useful representations in a deep network with a local denoising criterion
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Multivariate discrimination and the higgs+w/z search
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DELPHES 3, A modular framework for fast simulation of a generic collider experiment
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The automated computation of tree-level and next-to-leading order differential cross sections, and their matching to parton shower simulations
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Variational inference with normalizing flows
Danilo Rezende and Shakir Mohamed · 2015
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Siamese neural networks for one-shot image recognition
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Deepak Pathak et al · 2016
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Neural discrete representation learning
Aaron van den Oord, Oriol Vinyals, and Koray Kavukcuoglu · 2017
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Classification without labels: Learning from mixed samples in high energy physics
Eric M Metodiev, Benjamin Nachman, and Jesse Thaler · 2017
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Alec Radford et al · 2018
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Bert: Pre-training of deep bidirectional transformers for language understanding, 2019
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Bart: Denoising sequence-to-sequence pre-training for natural language generation, translation, and comprehension, 2019
Mike Lewis et al · 2019
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Language models are few-shot learners
Tom Brown et al · 2020
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A simple framework for contrastive learning of visual representations
Ting Chen et al · 2020
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Deep Sets based Neural Networks for Impact Parameter Flavour Tagging in ATLAS
ATLAS Collaboration · 2020
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Score-based generative modeling through stochastic differential equations, 2020
Yang Song et al · 2020
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On layer normalization in the transformer architecture
Ruibin Xiong et al · 2020
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Noam Shazeer · 2020
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Emerging properties in self-supervised vision transformers
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Zero-shot text-to-image generation
Aditya Ramesh and othersw · 2021
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Classifying anomalies through outer density estimation (cathode)
Anna Hallin et al · 2022
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Graph Neural Network Jet Flavour Tagging with the ATLAS Detector
ATLAS Collaboration · 2022
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Pre-training strategy using real particle collision data for event classification in collider physics
Tomoe Kishimoto et al · 2023
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Gpt-4 technical report, 2023
OpenAI · 2023
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normflows: A pytorch package for normalizing flows
Vincent Stimper et al · 2023
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Flow matching for generative modeling
Yaron Lipman et al · 2023
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Sehban Omer · 2021
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Going deeper with image transformers
Hugo Touvron et al · 2021
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Secondary vertex finding in jets with neural networks
Jonathan Shlomi et al · 2021
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Normformer: Improved transformer pretraining with extra normalization, 2021
Sam Shleifer et al · 2021
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Symmetries, safety, and self-supervision
Barry M. Dillon et al · 2022
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On the opportunities and risks of foundation models, 2022
Rishi Bommasani et al · 2022
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Diederik P. Kingma et al · 2023
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Diffusion models as masked autoencoders
Chen Wei et al · 2023
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Flow-enhanced transportation for anomaly detection
Tobias andothers Golling · 2023
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Learning to isolate muons in data
Edmund Witkowski, Benjamin Nachman, and Daniel Whiteson · 2023
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Re-simulation-based self-supervised learning for pre-training foundation models, 2024
Philip Harris et al · 2024
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Finetuning foundation models for joint analysis optimization in high energy physics
Matthias Vigl, Nicole Hartman, and Lukas Heinrich · 2024
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Omnijet- α \alpha : The first cross-task foundation model for particle physics, 2024
Joschka Birk, Anna Hallin, and Gregor Kasieczka · 2024
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Omnilearn: A method to simultaneously facilitate all jet physics tasks, 2024
Vinicius Mikuni and Benjamin Nachman · 2024
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Large-Scale Pretraining and Finetuning for Efficient Jet Classification in Particle Physics
Zihan Zhao et al · 2024
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DINOv2: Learning robust visual features without supervision
Maxime Oquab et al · 2024
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Fast high-resolution image synthesis with latent adversarial diffusion distillation, 2024
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Faster diffusion model with improved quality for particle cloud generation
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Vision transformers need registers
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Improving new physics searches with diffusion models for event observables and jet constituents
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Full phase space resonant anomaly detection
Erik Buhmann et al · 2024
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