Alternatives and similar repositories for strassennets:

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

• cc-hpc-itwm / TensorQuant
  ☆47Updated 4 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
• brain-research / mean-field-cnns
  ☆34Updated 5 years ago
• stevenygd / SWALP
  Code for paper "SWALP: Stochastic Weight Averaging forLow-Precision Training".
  ☆62Updated 5 years ago
• McDonnell-Lab / 1-bit-per-weight
  Training wide residual networks for deployment using a single bit for each weight
  ☆36Updated 4 years ago
• DNNToolBox / Net-Trim
  The latest version of Net-Trim which solves the actual constrained problem
  ☆24Updated 4 years ago
• team-approx-bayes / BayesBiNN
  Code for the paper "Training Binary Neural Networks with Bayesian Learning Rule
  ☆37Updated 3 years ago
• szagoruyko / binary-wide-resnet
  PyTorch implementation of Wide Residual Networks with 1-bit weights by McDonnell (ICLR 2018)
  ☆124Updated 6 years ago
• MatthieuCourbariaux / 8-bit-deep-learning
  Training neural networks with 8-bit computations
  ☆29Updated 8 years ago
• alecwangcq / EigenDamage-Pytorch
  Code for "EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis" https://arxiv.org/abs/1905.05934
  ☆112Updated 4 years ago
• masahi / tvm-winograd
  Test winograd convolution written in TVM for CUDA and AMDGPU
  ☆40Updated 6 years ago
• apaszke / torch-opCounter
  ☆28Updated 7 years ago
• mil-ad / studying-binary-neural-networks
  ☆53Updated 5 years ago
• KarenUllrich / Tutorial-SoftWeightSharingForNNCompression
  A tutorial on 'Soft weight-sharing for Neural Network compression' published at ICLR2017
  ☆145Updated 7 years ago
• amirgholami / HessianFlow
  ☆82Updated 5 years ago
• necludov / group-sparsity-sbp
  Structured Bayesian Pruning, NIPS 2017
  ☆73Updated 4 years ago
• forestagostinelli / Learned-Activation-Functions-Source
  For the reproduction of research by Agostinelli et al. Learning Activation Functions to Improve Deep Neural Networks. http://arxiv.org/ab…
  ☆19Updated 9 years ago
• hessamb / lcnn
  LCNN: Lookup-based Convolutional Neural Network
  ☆52Updated 7 years ago
• jiaweizzhao / signSGD-with-Majority-Vote
  ☆74Updated 5 years ago
• hyang1990 / model_based_energy_constrained_compression
  Code for paper "Energy-Constrained Compression for Deep Neural Networks via Weighted Sparse Projection and Layer Input Masking"
  ☆17Updated 5 years ago
• allenai / dnw
  Discovering Neural Wirings (https://arxiv.org/abs/1906.00586)
  ☆138Updated 4 years ago
• ucla-vision / entropy-sgd
  Lua implementation of Entropy-SGD
  ☆81Updated 6 years ago
• czhu95 / ternarynet
  Implementation for Trained Ternary Network.
  ☆108Updated 8 years ago
• xhzhao / PyTorch-MPI-DDP-example
  PyTorch-MPI-DDP-example
  ☆17Updated 6 years ago
• hantek / BinaryConnect
  Source code for ``Neural Networks with Few Multiplications'' published at ICLR 2016
  ☆81Updated 8 years ago
• adityaiitb / pyprof2
  PyProf2: PyTorch Profiling tool
  ☆82Updated 4 years ago
• lixilinx / psgd_tf
  Tensorflow implementation of preconditioned stochastic gradient descent
  ☆34Updated last year
• zhengwy888 / binary_ops
  ☆23Updated 8 years ago
• MatthieuCourbariaux / deep-learning-multipliers
  Training deep neural networks with low precision multiplications
  ☆63Updated 9 years ago
• leonardblier / alrao
  Implementation of "Learning with Random Learning Rates" in PyTorch.
  ☆102Updated 5 years ago