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09/12/2023
Flows for Flows: Morphing one Dataset into another with Maximum Likelihood Estimation
Many components of data analysis in high energy physics and beyond requi...
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07/13/2023
PC-Droid: Faster diffusion and improved quality for particle cloud generation
Building on the success of PC-JeDi we introduce PC-Droid, a substantiall...
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07/11/2023
Decorrelation using Optimal Transport
Being able to decorrelate a feature space from protected attributes is a...
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07/05/2023
ν^2-Flows: Fast and improved neutrino reconstruction in multi-neutrino final states with conditional normalizing flows
In this work we introduce ν^2-Flows, an extension of the ν-Flows method ...
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05/08/2023
CURTAINs Flows For Flows: Constructing Unobserved Regions with Maximum Likelihood Estimation
Model independent techniques for constructing background data templates ...
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04/28/2023
Flow Away your Differences: Conditional Normalizing Flows as an Improvement to Reweighting
We present an alternative to reweighting techniques for modifying distri...
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03/24/2023
Topological Reconstruction of Particle Physics Processes using Graph Neural Networks
We present a new approach, the Topograph, which reconstructs underlying ...
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03/09/2023
PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physics
In this paper, we present a new method to efficiently generate jets in H...
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11/04/2022
Flows for Flows: Training Normalizing Flows Between Arbitrary Distributions with Maximum Likelihood Estimation
Normalizing flows are constructed from a base distribution with a known ...
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11/04/2022
Decorrelation with conditional normalizing flows
The sensitivity of many physics analyses can be enhanced by constructing...
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05/30/2022
Flowification: Everything is a Normalizing Flow
We develop a method that can be used to turn any multi-layer perceptron ...
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02/10/2022
SUPA: A Lightweight Diagnostic Simulator for Machine Learning in Particle Physics
Deep learning methods have gained popularity in high energy physics for ...
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12/15/2021
Funnels: Exact maximum likelihood with dimensionality reduction
Normalizing flows are diffeomorphic, typically dimension-preserving, mod...
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05/03/2021
The Tracking Machine Learning challenge : Throughput phase
This paper reports on the second "Throughput" phase of the Tracking Mach...
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01/16/2021
Hashing and metric learning for charged particle tracking
We propose a novel approach to charged particle tracking at high intensi...
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07/03/2020
Variational Autoencoders for Anomalous Jet Tagging
We present a detailed study on Variational Autoencoders (VAEs) for anoma...
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07/08/2018