115 citations · 322 across the 12 of their papers we have counts for
8 papers · 1 filter
Apparent ice accumulation rate in East Antarctica: Relation with temperature and thinning pattern
Radhendushka Srivastava, Debasis Sengupta, Prosenjit Ghosh
We present here formal evidence of a strong linkage between temperature and East Antarctic ice accumulation over the past eight hundred kiloyears, after accounting for thinning. Th…
A semi-parametric model for assessing the effect of temperature on ice accumulation rate from Antarctic ice core data
Radhendushka Srivastava, Debasis Sengupta
In this paper, we present a semiparametric model for describing the effect of temperature on Antarctic ice accumulation on a paleoclimatic time scale. The model is motivated by sha…
PC-Droid: Faster diffusion and improved quality for particle cloud generation
Matthew Leigh, Debajyoti Sengupta, John Andrew Raine +2
Building on the success of PC-JeDi we introduce PC-Droid, a substantially improved diffusion model for the generation of jet particle clouds. By leveraging a new diffusion formulat…
The Interplay of Machine Learning--based Resonant Anomaly Detection Methods
Tobias Golling, Gregor Kasieczka, Claudius Krause +6
Machine learning--based anomaly detection (AD) methods are promising tools for extending the coverage of searches for physics beyond the Standard Model (BSM). One class of AD metho…
CURTAINs Flows For Flows: Constructing Unobserved Regions with Maximum Likelihood Estimation
Debajyoti Sengupta, Samuel Klein, John Andrew Raine +1
Model independent techniques for constructing background data templates using generative models have shown great promise for use in searches for new physics processes at the LHC. W…
Yield Strength-Plasticity Trade-Off and Uncertainty Quantification for Machine-learning-based Design of Refractory High-Entropy Alloys
Stephen A. Giles, Hugh Shortt, Peter K. Liaw +1
Development of process-structure-property relationships in materials science is an important and challenging frontier which promises improved materials and reduced time and cost in…
The Mass-ive Issue: Anomaly Detection in Jet Physics
Tobias Golling, Takuya Nobe, Dimitrios Proios +8
In the hunt for new and unobserved phenomena in particle physics, attention has turned in recent years to using advanced machine learning techniques for model independent searches.…
PC-JeDi: Diffusion for Particle Cloud Generation in High Energy Physics
Matthew Leigh, Debajyoti Sengupta, Guillaume Quétant +3
In this paper, we present a new method to efficiently generate jets in High Energy Physics called PC-JeDi. This method utilises score-based diffusion models in conjunction with tra…