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We propose a novel representation of virtual humans for highly realistic real-time animation and rendering in 3D applications. We learn pose dependent appearance and geometry from highly accurate dynamic mesh sequences obtained from…
Ultra-fast and multi-dimensional spectroscopy gives a powerful looking glass into the dynamics of molecular systems. In particular two-dimensional electronic spectroscopy (2DES) provides a probe of coherence and the flow of energy within…
Deterministic Lateral Displacement (DLD) devices are widely used in microfluidics for label-free, size-based separation of particles and cells, with particular promise in isolating circulating tumor cells (CTCs) for early cancer…
As charged particle bunches become shorter and more intense, the effects of nonlinear intra-bunch collective interactions such as space charge forces and bunch-to-bunch influences such as wakefields and coherent synchrotron radiation also…
For the proper operation of Dalian Compact Light Source (DCLS) linac, measurement and control of the electron bunch is critical. In order to test control algorithms and high level physical applications, a virtual accelerator environment is…
Here we describe the implementation and calibration of a streaked visible spectrometer (SVS) for optical pyrometry and emission/absorption spectroscopy on light gas gun platforms in the UC Davis Shock Compression Laboratory. The diagnostic…
Modern accelerator front ends almost exclusively include radio-frequency quadrupoles for initial capture and focusing of the low-energy beam. Dynamics in the RFQ define the longitudinal bunch parameters. Simulation of the SNS RFQ with…
Ultrasound shear wave elasticity imaging is a valuable tool for quantifying the elastic properties of tissue. Typically, the shear wave velocity is derived and mapped to an elasticity value, which neglects information such as the shape of…
Prognostic models aim to predict the future course of a disease or condition and are a vital component of personalized medicine. Statistical models make use of longitudinal data to capture the temporal aspect of disease progression;…
Autonomous synthesis and characterization of inorganic materials requires the automatic and accurate analysis of X-ray diffraction spectra. For this task, we designed a probabilistic deep learning algorithm to identify complex multi-phase…
We present a deep learning solution for estimating the incident illumination at any 3D location within a scene from an input narrow-baseline stereo image pair. Previous approaches for predicting global illumination from images either…
Background: In medical imaging, images are usually treated as deterministic, while their uncertainties are largely underexplored. Purpose: This work aims at using deep learning to efficiently estimate posterior distributions of imaging…
This paper proposes an efficient and probabilistic adaptive voxel mapping method for LiDAR odometry. The map is a collection of voxels; each contains one plane (or edge) feature that enables the probabilistic representation of the…
Deploying advanced imaging solutions to robotic and autonomous systems by mimicking human vision requires simultaneous acquisition of multiple fields of views, named the peripheral and fovea regions. Low-resolution peripheral field provides…
A basic challenge in experimental physics is the extraction of information related to variables that are not directly measured. The challenge is particularly severe in quantum systems where one may be interested in correlations of operators…
This lecture gives an overview about beam diagnostics techniques for the characterization of electron bunches obtained with plasma accelerators. Due to the limited space, the lecture does not aim to go into the specifics of the single…
Proton FLASH therapy leverages ultra-high dose-rate radiation to enhance the sparing of organs at risk without compromising tumor control probability. To prepare for the delivery of high doses to targets, we aim to develop a deep…
We have recently developed a method based on relativistic time-dependent density functional theory (TD-DFT) that allows the calculation of electronic spectra in solution (Creutzberg, Hedeg{\aa}rd, J. Chem. Theory Comput.18, 2022, 3671).…
Long-term 3D map management is a fundamental capability required by a robot to reliably navigate in the non-stationary real-world. This paper develops open-source, modular, and readily available LiDAR-based lifelong mapping for urban sites.…
This paper proposes a novel multimodal deep learning framework integrating bidirectional LSTM, multi-head attention mechanism, and variational mode decomposition (BiLSTM-AM-VMD) for early liver cancer diagnosis. Using heterogeneous data…