Pinned Repositories
ANIML
Reproduction of "Model-Agnostic Meta-Learning" (MAML) and "Reptile".
aTEAM
A pyTorch Extension for Applied Mathematics
awesome-semantic-segmentation-pytorch
Semantic Segmentation on PyTorch (include FCN, PSPNet, Deeplabv3, Deeplabv3+, DANet, DenseASPP, BiSeNet, EncNet, DUNet, ICNet, ENet, OCNet, CCNet, PSANet, CGNet, ESPNet, LEDNet, DFANet)
classifier-pruner
Using Network-Slimming to prune classifier
Convolutional_LSTM_PyTorch
Multi-layer convolutional LSTM with Pytorch
ddfnet
The official implementation of the CVPR2021 paper: Decoupled Dynamic Filter Networks
Discover-PDE-with-Noisy-Scarce-Data
ICLR2022: Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning
distiller
Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://nervanasystems.github.io/distiller
efficient_densenet_pytorch
A memory-efficient implementation of DenseNets
yolov3-prune
prune filters and layers for yolov3
huangxiang360729's Repositories
huangxiang360729/yolov3-prune
prune filters and layers for yolov3
huangxiang360729/classifier-pruner
Using Network-Slimming to prune classifier
huangxiang360729/aTEAM
A pyTorch Extension for Applied Mathematics
huangxiang360729/awesome-semantic-segmentation-pytorch
Semantic Segmentation on PyTorch (include FCN, PSPNet, Deeplabv3, Deeplabv3+, DANet, DenseASPP, BiSeNet, EncNet, DUNet, ICNet, ENet, OCNet, CCNet, PSANet, CGNet, ESPNet, LEDNet, DFANet)
huangxiang360729/Convolutional_LSTM_PyTorch
Multi-layer convolutional LSTM with Pytorch
huangxiang360729/ddfnet
The official implementation of the CVPR2021 paper: Decoupled Dynamic Filter Networks
huangxiang360729/Discover-PDE-with-Noisy-Scarce-Data
ICLR2022: Discovering Nonlinear PDEs from Scarce Data with Physics-encoded Learning
huangxiang360729/distiller
Neural Network Distiller by Intel AI Lab: a Python package for neural network compression research. https://nervanasystems.github.io/distiller
huangxiang360729/efficient_densenet_pytorch
A memory-efficient implementation of DenseNets
huangxiang360729/fastmoe
A fast MoE impl for PyTorch
huangxiang360729/FCNVMB-Deep-learning-based-seismic-velocity-model-building
Deep-learning inversion: A next-generation seismic velocity model building method
huangxiang360729/FDTD-1D-2D-3D-
FDTDsimulation,1D,2D,3D
huangxiang360729/fourier_neural_operator
Use Fourier transform to learn operators in differential equations.
huangxiang360729/galerkin-transformer
[NeurIPS 2021] Galerkin Transformer: a linear attention without softmax
huangxiang360729/GNN_Review
GNN综述阅读报告
huangxiang360729/Graphormer
Graphormer is a general-purpose deep learning backbone for molecular modeling.
huangxiang360729/img-storage
img storage for other repository
huangxiang360729/mixture-of-experts
PyTorch Re-Implementation of "The Sparsely-Gated Mixture-of-Experts Layer" by Noam Shazeer et al. https://arxiv.org/abs/1701.06538
huangxiang360729/mscalednn
huangxiang360729/OpenFWI
A collection of codes with OpenFWI project
huangxiang360729/PDE-Net
PDE-Net: Learning PDEs from Data
huangxiang360729/PDEBench
PDEBench: An Extensive Benchmark for Scientific Machine Learning
huangxiang360729/PeRCNN
Physics-encoded recurrent convolutional neural network
huangxiang360729/pinns_for_point_source_IJCAI2022
A Universal PINNs Method for Solving Partial Differential Equations with a Point Source
huangxiang360729/pygcn
Graph Convolutional Networks in PyTorch
huangxiang360729/pytorch-cifar
95.16% on CIFAR10 with PyTorch
huangxiang360729/PyTorch-Learning-Rate-Scheduler
torch.optim.lr_scheduler
huangxiang360729/Reinforcement-learning-with-Pytorch
Using Pytorch to implement Reinforcement learning demo
huangxiang360729/Unsupervised_Deep_Learning_of_Incompressible_Fluid_Dynamics
huangxiang360729/yolov3-channel-and-layer-pruning
yolov3 yolov4 channel and layer pruning, Knowledge Distillation 层剪枝，通道剪枝，知识蒸馏