research
∙
09/15/2023
Ensuring Toplogical Data-Structure Preservation under Autoencoder Compression due to Latent Space Regularization in Gauss–Legendre nodes
We formulate a data independent latent space regularisation constraint f...
share
research
∙
02/27/2023
Learning Electron Bunch Distribution along a FEL Beamline by Normalising Flows
Understanding and control of Laser-driven Free Electron Lasers remain to...
research
∙
12/16/2022
LiFe-net: Data-driven Modelling of Time-dependent Temperatures and Charging Statistics Of Tesla's LiFePo4 EV Battery
Modelling the temperature of Electric Vehicle (EV) batteries is a fundam...
research
∙
12/12/2022
Implicit Neural Convolutional Kernels for Steerable CNNs
Steerable convolutional neural networks (CNNs) provide a general framewo...
research
∙
12/12/2022
Acceptance Rates of Invertible Neural Networks on Electron Spectra from Near-Critical Laser-Plasmas: A Comparison
While the interaction of ultra-intense ultra-short laser pulses with nea...
research
∙
11/09/2022
Continual learning autoencoder training for a particle-in-cell simulation via streaming
The upcoming exascale era will provide a new generation of physics simul...
research
∙
10/04/2022
Amortized Bayesian Inference of GISAXS Data with Normalizing Flows
Grazing-Incidence Small-Angle X-ray Scattering (GISAXS) is a modern imag...
research
∙
06/04/2022
Learning Generative Factors of Neuroimaging Data with Variational auto-encoders
Neuroimaging techniques produce high-dimensional, stochastic data from w...
research
∙
06/04/2022
Investigating Brain Connectivity with Graph Neural Networks and GNNExplainer
Functional connectivity plays an essential role in modern neuroscience. ...
research
∙
12/10/2021
Global Attention Mechanism: Retain Information to Enhance Channel-Spatial Interactions
A variety of attention mechanisms have been studied to improve the perfo...
research
∙
11/24/2021
NAM: Normalization-based Attention Module
Recognizing less salient features is the key for model compression. Howe...
research
∙
06/01/2021
Invertible Surrogate Models: Joint surrogate modelling and reconstruction of Laser-Wakefield Acceleration by invertible neural networks
Invertible neural networks are a recent technique in machine learning pr...
research
∙
06/01/2021
Data-Driven Shadowgraph Simulation of a 3D Object
In this work we propose a deep neural network based surrogate model for ...
research
∙
09/08/2020
Large-scale Neural Solvers for Partial Differential Equations
Solving partial differential equations (PDE) is an indispensable part of...
research
∙
01/26/2020
Visualisation of Medical Image Fusion and Translation for Accurate Diagnosis of High Grade Gliomas
The medical image fusion combines two or more modalities into a single v...
research
∙
08/11/2019
Structural Similarity based Anatomical and Functional Brain Imaging Fusion
Multimodal medical image fusion helps in combining contrasting features ...
research
∙
11/02/2018
