Alternatives and similar repositories for tensorflow_dense_op

Users that are interested in tensorflow_dense_op are comparing it to the libraries listed below

• jrk / gradient-halide
  ☆102Updated 5 years ago
• NVlabs / condensa
  Programmable Neural Network Compression
  ☆148Updated 3 years ago
• davidstutz / tensorflow-cpp-op-example
  Simple example of implementing a new Tensorflow operation and its gradient in C++.
  ☆56Updated 6 years ago
• fpeder / espresso
  Efficient forward propagation for BCNNs
  ☆50Updated 8 years ago
• LsNatan / NICE
  This code implements NICE papper
  ☆20Updated 6 years ago
• ChanganVR / ConstraintAwareCompression
  [ECCV18] Constraint-Aware Deep Neural Network Compression
  ☆12Updated 6 years ago
• szagoruyko / binary-wide-resnet
  PyTorch implementation of Wide Residual Networks with 1-bit weights by McDonnell (ICLR 2018)
  ☆126Updated 6 years ago
• sniklaus / pytorch-extension
  an example of a CUDA extension for PyTorch using CuPy which computes the Hadamard product of two tensors
  ☆118Updated 2 months ago
• chrischoy / MakePytorchPlusPlus
  How and why you want to make your pytorch CUDA/CPP extension with a Makefile
  ☆172Updated 6 years ago
• kaiqzhan / ADAM-ADMM
  A Unified, Systematic Framework of Structured Weight Pruning for DNNs
  ☆22Updated 7 years ago
• ARM-software / scalpel
  This is a PyTorch implementation of the Scalpel. Node pruning for five benchmark networks and SIMD-aware weight pruning for LeNet-300-100…
  ☆41Updated 6 years ago
• szagoruyko / pyinn
  CuPy fused PyTorch neural networks ops
  ☆273Updated 7 years ago
• zhuwenxi / pytorch-profiling-tool
  ☆54Updated 7 years ago
• ppwwyyxx / FRN-on-common-ImageNet-baseline
  Filter Response Normalization tested on better ImageNet baselines.
  ☆35Updated 5 years ago
• wenwei202 / autogrow
  AutoGrow: Automatic Layer Growing in Deep Convolutional Networks (KDD 2020)
  ☆39Updated 6 years ago
• Connor323 / Convolution-with-sparse-kernel-in-TF
  Development a customized op in TensorFlow for convolution with sparse kernel
  ☆28Updated 6 years ago
• caiwenpu / Compression_Paper
  ☆46Updated 5 years ago
• xingyul / sparse-winograd-cnn
  Efficient Sparse-Winograd Convolutional Neural Networks (ICLR 2018)
  ☆191Updated 6 years ago
• cc-hpc-itwm / TensorQuant
  ☆47Updated 5 years ago
• brais-martinez / real2binary
  Code for the ICLR2020 "Training Binary Neural Networks with Real-to-Binary Convolutions
  ☆35Updated 5 years ago
• Mxbonn / INQ-pytorch
  A PyTorch implementation of "Incremental Network Quantization: Towards Lossless CNNs with Low-Precision Weights"
  ☆167Updated 5 years ago
• EunhyeokPark / script_for_WQ
  ☆13Updated 8 years ago
• jnjaby / Model-Compression-Acceleration
  Paper list on model compression and acceleration
  ☆26Updated 6 years ago
• 1adrianb / binary-nas
  ☆35Updated 5 years ago
• stevenygd / SWALP
  Code for paper "SWALP: Stochastic Weight Averaging forLow-Precision Training".
  ☆62Updated 6 years ago
• istoony / winograd-convolutional-nn
  I'm going to use the Winograd’s minimal filtering algorithms to introduce a new class of fast algorithms for convolutional neural networks…
  ☆12Updated 7 years ago
• statsml / compress-net-notes
  ☆20Updated 7 years ago
• eladhoffer / quantized.pytorch
  ☆213Updated 6 years ago
• andyhahaha / Convolutional-Neural-Network-Compression-Survey
  ☆34Updated 8 years ago
• McDonnell-Research-Lab / 1-bit-per-weight
  Training wide residual networks for deployment using a single bit for each weight - Official Code Repository for ICLR 2018 Published Pape…
  ☆37Updated 5 years ago