Name: Xiangming Meng
Type: User
Company: Zhejiang University
Bio: Assistant Professor at The Zhejiang University-University of Illinois Urbana-Champaign Institute (ZJUI), Zhejiang University
Location: Zhejiang, China
Blog: https://mengxiangming.github.io/
Xiangming Meng's Projects
Graph Markov Neural Networks
Must-read papers on graph neural networks (GNN)
Algorithms for Learning Graphical Models
Code to reproduce results in our paper "Sparse Logistic Regression Learns All Discrete Pairwise Graphical Models".
PyTorch implementation of a Variational Autoencoder with Gumbel-Softmax Distribution
Hopfield Networks is All You Need
Downloader from ImageNet Image URLs
Laplace approximations for Deep Learning.
Lasso Regression Tutorials
PyTorch Meta-learning Framework for Researchers
Interaction Screening and Pseudolikelihood based algorithms for learning dynamics of Ising model
Source code from the NeurIPS 2019 workshop article "Keep It Simple: Graph Autoencoders Without Graph Convolutional Networks" (G. Salha, R. Hennequin, M. Vazirgiannis) + k-core framework implementation from IJCAI 2019 article "A Degeneracy Framework for Scalable Graph Autoencoders" (G. Salha, R. Hennequin, V.A. Tran, M. Vazirgiannis)
Template and style files for ICLR
my personal website
The code for the paper, 'Meta-Curvature, Eunbyung Park and Junier Oliver, NeurIPS 2019'
Murphy's Machine Learning: A Probabilistic Perspective Errata (4th and later printings)
neuronal message passing
NN-GRISE: Code for reproducibility
Tutorial on normalizing flows.
Code for experiments in my blog post on the Neural Tangent Kernel: https://rajatvd.github.io/NTK
Proximal Mean-field for Neural Network Quantization
PRML algorithms implemented in Python
Matlab code for machine learning algorithms in book PRML
Lightning Talk about sacred at PyData Berlin
Graph Convolutional Networks in PyTorch
95.16% on CIFAR10 with PyTorch
Gradually-Warmup Learning Rate Scheduler for PyTorch
Multi GPU Training Code for Deep Learning with PyTorch