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Wang Bomin's Projects

st-gcn icon st-gcn

Spatial Temporal Graph Convolutional Networks (ST-GCN) for Skeleton-Based Action Recognition in PyTorch

stgat icon stgat

Implementation of Spatial-Temporal Graph Attention Networks for Traffic Flow Forecasting(for IJCAI 2020)

structpool icon structpool

The code for our ICLR paper: StructPool: Structured Graph Pooling via Conditional Random Fields

subnetwork-inference icon subnetwork-inference

Code for "Bayesian Deep Learning via Subnetwork Inference" (https://arxiv.org/abs/2010.14689)

sugar icon sugar

Code for "SUGAR: Subgraph Neural Network with Reinforcement Pooling and Self-Supervised Mutual Information Mechanism""

supergat icon supergat

Official implementation of Self-supervised Graph Attention Networks (SuperGAT), ICLR 2021.

surface-loss icon surface-loss

Code for our MIDL 2019 submission https://openreview.net/forum?id=S1gTA5VggE

swa_gaussian icon swa_gaussian

Code repo for "A Simple Baseline for Bayesian Uncertainty in Deep Learning"

syn2real icon syn2real

Syn2Real Transfer Learning for Image Deraining using Gaussian Processes

tbn icon tbn

TBNv2: Convolutional Neural Network With Ternary Inputs and Binary Weights

tdv icon tdv

Total Deep Variation Regularizer

tenet icon tenet

Official Pytorch Implementation for Trinity of Pixel Enhancement: a Joint Solution for Demosaicing, Denoising and Super-Resolution

tent icon tent

ICLR21 Tent: Fully Test-Time Adaptation by Entropy Minimization

ternaryfeaturemasks icon ternaryfeaturemasks

Implementation of "Ternary Feature Masks: zero-forgetting for task-incremental learning"

tf_unet icon tf_unet

Generic U-Net Tensorflow implementation for image segmentation

tgg-pytorch icon tgg-pytorch

The source code for our ACM MM 2019 paper "TGG: Transferable Graph Generation for Zero-shot and Few-shot Learning".

torchdiffeq icon torchdiffeq

Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.

torchgan icon torchgan

Research Framework for easy and efficient training of GANs based on Pytorch

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