Related papers: PE-GAN: Prior Embedding GAN for PXD images at Bell…
High backgrounds and detector ageing impact the track finding in the Belle II central drift chamber, reducing both track purity and track efficiency in events. This necessitates the development of new track finding algorithms to mitigate…
We describe a neural network for predicting the background hit rate in the Belle II detector produced by the SuperKEKB electron-positron collider. The neural network, BGNet, learns to predict the individual contributions of different…
The new Belle II experiment at the asymmetric $e^+ e^-$ accelerator SuperKEKB at KEK in Japan is designed to deliver a peak luminosity of $8\times10^{35}\text{cm}^{-2}\text{s}^{-1}$. To perform high-precision track reconstruction, e.g. for…
2D images are observations of the 3D physical world depicted with the geometry, material, and illumination components. Recovering these underlying intrinsic components from 2D images, also known as inverse rendering, usually requires a…
For the Belle II experiment at KEK (Tsukuba, Japan) the KEKB accelerator was upgraded to deliver a 40 times larger instantaneous luminosity than before, which requires an increased radiation hardness of the detector components. As the…
We propose PD-GAN, a probabilistic diverse GAN for image inpainting. Given an input image with arbitrary hole regions, PD-GAN produces multiple inpainting results with diverse and visually realistic content. Our PD-GAN is built upon a…
The Belle II experiment currently under construction at the $e^+e^-$-collider SuperKEKB in Japan is designed to explore new physics beyond the standard model with an approximately 50 times larger data sample compared to its predecessor. The…
Recent advances in generative adversarial networks (GANs) have achieved great success in automated image composition that generates new images by embedding interested foreground objects into background images automatically. On the other…
In 2019 the Belle II experiment started data taking at the asymmetric SuperKEKB collider (KEK, Japan) operating at the Y(4S) resonance. Belle II will search for new physics beyond the Standard Model by collecting an integrated luminosity of…
We present the study of an end-to-end multi-track reconstruction algorithm for the central drift chamber of the Belle II experiment at the SuperKEKB collider using Graph Neural Networks for an unknown number of particles. The algorithm uses…
The projected gradient descent (PGD) method has shown to be effective in recovering compressed signals described in a data-driven way by a generative model, i.e., a generator which has learned the data distribution. Further reconstruction…
Generative Adversarial Networks (GANs) have proven successful for unsupervised image generation. Several works have extended GANs to image inpainting by conditioning the generation with parts of the image to be reconstructed. Despite their…
In this paper, we propose a generative adversarial network (GAN)-based hyperspectral anomaly detection algorithm. In the proposed algorithm, we train a GAN model to generate a synthetic background image which is close to the original…
The PandaX dark matter detection project searches for dark matter particles using the technology of dual phase xenon time projection chamber. The low expected rate of the signal events makes the control of backgrounds crucial for the…
Network embedding has become a hot research topic recently which can provide low-dimensional feature representations for many machine learning applications. Current work focuses on either (1) whether the embedding is designed as an…
Conditional Generative Adversarial Networks (cGANs) extend the standard unconditional GAN framework to learning joint data-label distributions from samples, and have been established as powerful generative models capable of generating…
The future Belle II experiment will employ a computer-farm based data reduction system for the readout of its innermost detector, a DEPFET-technology based silicon detector with pixel readout. A large fraction of the background hits can be…
In this paper, we address the problem of generating person images conditioned on both pose and appearance information. Specifically, given an image xa of a person and a target pose P(xb), extracted from a different image xb, we synthesize a…
The physics goals the Belle II experiment require an exceptionally good alignment of all the components of the Belle II tracker. The Belle II tracker is composed of the DEPFET based pixel silicon detector, four layers of double sided…
We introduce BSD-GAN, a novel multi-branch and scale-disentangled training method which enables unconditional Generative Adversarial Networks (GANs) to learn image representations at multiple scales, benefiting a wide range of generation…