Alternatives and similar repositories for GrOWL

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

• KarenUllrich / Tutorial_BayesianCompressionForDL
  A tutorial on "Bayesian Compression for Deep Learning" published at NIPS (2017).
  ☆206Updated 7 years ago
• afriesen / ftprop
  Feasible target propagation code for the paper "Deep Learning as a Mixed Convex-Combinatorial Optimization Problem" by Friesen & Domingos…
  ☆28Updated 7 years ago
• necludov / group-sparsity-sbp
  Structured Bayesian Pruning, NIPS 2017
  ☆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"
  ☆18Updated 6 years ago
• amirgholami / HessianFlow
  ☆83Updated 6 years ago
• jaehong31 / CGES
  Combined Group and Exclusive Sparsity for Deep Neural Networks, ICML 2017
  ☆31Updated 7 years ago
• houlu369 / Loss-aware-Binarization
  Implementation of ICLR 2017 paper "Loss-aware Binarization of Deep Networks"
  ☆20Updated 6 years ago
• ucla-vision / entropy-sgd
  Lua implementation of Entropy-SGD
  ☆81Updated 7 years ago
• han-cai / PathLevel-EAS
  Path-Level Network Transformation for Efficient Architecture Search, in ICML 2018.
  ☆112Updated 7 years ago
• eugenium / layerCNN
  ☆20Updated 6 years ago
• csyhhu / L-OBS
  Codes for Layer-wise Optimal Brain Surgeon
  ☆78Updated 7 years ago
• jiaweizzhao / signSGD-with-Majority-Vote
  ☆77Updated 6 years ago
• anokland / local-loss
  PyTorch code for training neural networks without global back-propagation
  ☆167Updated 6 years ago
• rahulkidambi / AccSGD
  Implements pytorch code for the Accelerated SGD algorithm.
  ☆215Updated 7 years ago
• huangleiBuaa / OthogonalWN
  This project is the Torch implementation of our accepted AAAI 2018 paper : orthogonal weight normalization method for solving orthogonali…
  ☆57Updated 6 years ago
• ruihangdu / PyTorch-Deep-Compression
  A PyTorch implementation of the iterative pruning method described in Han et. al. (2015)
  ☆40Updated 7 years ago
• KarenUllrich / Tutorial-SoftWeightSharingForNNCompression
  A tutorial on 'Soft weight-sharing for Neural Network compression' published at ICLR2017
  ☆147Updated 8 years ago
• titu1994 / progressive-neural-architecture-search
  Implementation of Progressive Neural Architecture Search in Keras and Tensorflow
  ☆118Updated 6 years ago
• stevenygd / SWALP
  Code for paper "SWALP: Stochastic Weight Averaging forLow-Precision Training".
  ☆62Updated 6 years ago
• VITA-Group / Deep-K-Means-pytorch
  [ICML 2018] "Deep k-Means: Re-Training and Parameter Sharing with Harder Cluster Assignments for Compressing Deep Convolutions"
  ☆152Updated 4 years ago
• kirthevasank / nasbot
  Neural Architecture Search with Bayesian Optimisation and Optimal Transport
  ☆135Updated 7 years ago
• yaroslavvb / kfac_pytorch
  ☆135Updated 8 years ago
• alecwangcq / EigenDamage-Pytorch
  Code for "EigenDamage: Structured Pruning in the Kronecker-Factored Eigenbasis" https://arxiv.org/abs/1905.05934
  ☆113Updated 5 years ago
• mil-ad / studying-binary-neural-networks
  ☆52Updated 6 years ago
• AMLab-Amsterdam / L0_regularization
  Learning Sparse Neural Networks through L0 regularization
  ☆248Updated 5 years ago
• wendazhou / nnet-compression-generalization
  ☆27Updated 7 years ago
• han-cai / EAS
  Efficient Architecture Search by Network Transformation, in AAAI 2018
  ☆168Updated 6 years ago
• allenbai01 / ProxQuant
  ProxQuant: Quantized Neural Networks via Proximal Operators
  ☆30Updated 6 years ago
• TropComplique / trained-ternary-quantization
  Reducing the size of convolutional neural networks
  ☆112Updated 8 years ago
• team-approx-bayes / BayesBiNN
  Code for the paper "Training Binary Neural Networks with Bayesian Learning Rule
  ☆40Updated 4 years ago