相关论文: PC-JeDi: Diffusion for Particle Cloud Generation i…
Predicting the outcome of jet-milling based on the knowledge of process parameters and starting material properties is a task still far from being accomplished. Given the technical difficulties in measuring thermodynamics, flow properties…
Generative modeling has drawn much attention in creative and scientific data generation tasks. Score-based Diffusion Models, a type of generative model that iteratively learns to denoise data, have shown state-of-the-art results on tasks…
We propose a novel point cloud U-Net diffusion architecture for 3D generative modeling capable of generating high-quality and diverse 3D shapes while maintaining fast generation times. Our network employs a dual-branch architecture,…
The transverse momentum distributions of jets produced in p-p, p-\bar p, d-Au, Au-Au, and Pb-Pb collisions at high energies with different selected conditions are analyzed by using a multi-source thermal model. The multi-component (mostly…
Predictions are made for the jet substructure of one-jet events produced in electron-proton neutral current deep inelastic scattering at the future Electron-Ion Collider for exchanged four-momentum squared, $Q^2 > 125$ GeV$^2$. Data are…
In light of the widespread success of generative models, a significant amount of research has gone into speeding up their sampling time. However, generative models are often sampled multiple times to obtain a diverse set incurring a cost…
The advent of high-energy hadron colliders necessitates efficient and accurate computation of multi-jet production processes, both as QCD processes in their own right and as backgrounds for other physics. The algorithm that performs these…
Diffusion models for image generation function by progressively adding noise to an image set and training a model to separate out the signal from the noise. The noise profile used by these models is white noise -- that is, noise based on…
We introduce a general framework for solving partial differential equations (PDEs) using generative diffusion models. In particular, we focus on the scenarios where we do not have the full knowledge of the scene necessary to apply classical…
The design of aerodynamic shapes, such as airfoils, has traditionally required significant computational resources and relied on predefined design parameters, which limit the potential for novel shape synthesis. In this work, we introduce a…
While diffusion models have shown great success in image generation, their noise-inverting generative process does not explicitly consider the structure of images, such as their inherent multi-scale nature. Inspired by diffusion models and…
Accurate seismic velocity estimations are vital to understanding Earth's subsurface structures, assessing natural resources, and evaluating seismic hazards. Machine learning-based inversion algorithms have shown promising performance in…
Machine learning has demonstrated remarkable promise for solving the trajectory generation problem and in paving the way for online use of trajectory optimization for resource-constrained spacecraft. However, a key shortcoming in current…
Jets are produced by processes involving high momentum transfer of initial partons at high energies. Comparing jet production in pp and nucleus-nucleus collisions will allow us to study the jet-quenching effect caused by the hot and dense…
We introduce two diffusion models and an autoregressive transformer for LHC physics simulations. Bayesian versions allow us to control the networks and capture training uncertainties. After illustrating their different density estimation…
Ship design is a complex design process that may take a team of naval architects many years to complete. Improving the ship design process can lead to significant cost savings, while still delivering high-quality designs to customers. A new…
In this paper, we propose an efficient, fast, and versatile distillation method to accelerate the generation of pre-trained diffusion models: Flash Diffusion. The method reaches state-of-the-art performances in terms of FID and CLIP-Score…
Recent advances in diffusion models have driven remarkable progress in image generation. However, the generation process remains computationally intensive, and users often need to iteratively refine prompts to achieve the desired results,…
Collisions of heavy ion nuclei at relativistic speeds (close to the speed of light) creates a high temperature and very dense form of matter, now known to consist of de-confined quarks and gluons, named the quark gluon plasma (QGP). In this…
Jet and particle production have been studied in collisions of quasi-real photons collected during the LEP2 program. OPAL and DELPHI report good agreement of NLO perturbative QCD with the measured differential di-jet cross sections, which…