Name: Cong Xiao
Type: User
Company: Delft University of Technology
Bio: Short CV:
2013-2016, M.Sc. in Oil & Gas Field Development Engineering at China University of Petroleum,Beijing,China
2016-Present, Ph.D in Applied Mathematics
Location: Delft, The Netherlands
Blog: https://www.tudelft.nl/ewi/over-de-faculteit/afdelingen/applied-mathematics/mathematical-physics/people/x-cong/
Cong Xiao's Projects
This is a repository containing code to Paper "Optimized High Resolution 3D Dense-U-Net Network for Brain and Spine Segmentation" published at MDPI Applied sciences journal - https://www.mdpi.com/2076-3417/9/3/404 .
3D ResNets for Action Recognition (CVPR 2018)
Deep Neural Networks for Map-Based 4D Seismic Pressure-Saturation Inversion
Automatic Differentiation Library for Computational and Mathematical Engineering
An adversarial autoencoder implementation in pytorch
Attention Based Spatial-Temporal Graph Convolutional Networks for Traffic Flow Forecasting (ASTGCN) AAAI 2019
This is the repository for the Auto-BEL implementation in Python
A curated list of automated machine learning papers, articles, tutorials, slides and projects
Curated from repositories that make our lives as geoscientists, hackers and data wranglers easier or just more awesome
A comprehensive list of pytorch related content on github,such as different models,implementations,helper libraries,tutorials etc.
Papers for Bayesian-NN
BCDU-Net : Medical Image Segmentation
Bayesian Evidential Deep Learning with PAC Regularization
Homepage for STAT 157 at UC Berkeley
This Pytorch repo uses BiConvLSTM in a Spatiotemporal Encoder to detect violence in Videos. Three benchmark datasets namely Hockey, Movies and Violent Flows were used in this work.
Bidirectional (Symmetrical) Deep Neural Networks
Deep residual networks for dimensionality reduction and surrogate modeling in high-dimensional inverse problems
A framework for collaborative analysis of distributed environmental data (web user interface package)
Conditional Deep Convolutional Generative Adversarial Networks structure for completing incomplete face images and furthermore classifying.
Conditional Deep Convolutional GAN
Deep autoregressive neural networks for high-dimensional inverse problems
Bayesian deep convolutional encoder-decoder networks for surrogate modeling and uncertainty quantification
Numerical Black-Box Optimization Benchmarking Framework
This is the codes and examples described in "Mo, S., Lu, D., Shi, X., Zhang, G., Ye, M., Wu, J., & Wu, J. (2017). A Taylor expansion‐based adaptive design strategy for global surrogate modeling with applications in groundwater modeling. Water Resources Research, 53, 10,802–10,823. https://doi.org/10.1002/2017WR021622"
Convolutional Encoder Decoder network based on the SegNet architecture for unsupervised feature learning
Implementation of bi-directional Conv LSTM and Conv GRU in PyTorch.