Alternatives and similar repositories for exploring-loss

Users that are interested in exploring-loss are comparing it to the libraries listed below

• artix41 / AVO-pytorch
  Implementation of Adversarial Variational Optimization in PyTorch
  ☆43Updated 6 years ago
• e-lab / pytorch-CortexNet
  ☆44Updated 7 years ago
• AtheMathmo / AggMo
  Code for "Aggregated Momentum: Stability Through Passive Damping", Lucas et al. 2018
  ☆34Updated 6 years ago
• ajbrock / BoilerPlate
  Odds and Ends and Things I've implemented.
  ☆78Updated 6 years ago
• yuandong-tian / ICML17_ReLU
  ☆29Updated 8 years ago
• songhan / SqueezeNet-DSD-Training
  ☆57Updated 7 years ago
• maga33 / TransferNet
  A Caffe implementation of http://arxiv.org/abs/1512.07928
  ☆39Updated 9 years ago
• gyglim / dvn
  Reference implementation for Structured Prediction with Deep Value Networks
  ☆55Updated 7 years ago
• hardikbansal / DiracNets
  ☆22Updated 8 years ago
• shreyassaxena / convolutional-neural-fabrics
  Architecture learning for CNN's
  ☆37Updated 8 years ago
• masabdi / multi-resnet
  Multi-Residual Networks
  ☆23Updated 8 years ago
• mathieuaubry / features_analysis
  Implementation of the approach described in "Understanding deep features with computer-generated imagery" , M. Aubry and B. Russell, ICCV…
  ☆21Updated last year
• lballes / msvag
  TensorFlow implementation of (Momentum) Stochastic Variance-Adapted Gradient.
  ☆44Updated 7 years ago
• arayabrain / FewshotClassifier
  Code for the blog post on few-shot classification via task representation and communication.
  ☆18Updated 8 years ago
• pranv / ARC
  Code for Attentive Recurrent Comparators
  ☆57Updated 8 years ago
• fvisin / main_loop_tf
  A main loop based on dataset loaders
  ☆15Updated 7 years ago
• vabh / convolutional-neural-fabrics
  PyTorch implementation of Convolutional Neural Fabrics http://arxiv.org/abs/1606.02492
  ☆25Updated 8 years ago
• jhoffman / lsda
  Large scale detection through adaptation
  ☆47Updated 5 years ago
• ShayanPersonal / checkered-cnn
  A new technique to increase receptive field in convolutional neural networks without losing so much information.
  ☆30Updated 7 years ago
• gaohuang / DenseNet_lite
  A more memory efficient Torch implementation of "Densely Connected Convolutional Networks".
  ☆29Updated 8 years ago
• Kaixhin / Dist-A3C
  Distributed A3C
  ☆34Updated 7 years ago
• szagoruyko / idiap-tutorials
  ☆16Updated 8 years ago
• singlasahil14 / orthogonal-convolution
  Github repo for my experiments with the orthogonal convolution idea
  ☆22Updated 7 years ago
• e-lab / torch-prednet
  ☆19Updated 8 years ago
• kbullaughey / dni-synthetic-gradients
  Torch implementation reproducing MNIST experiments from DeepMind's DNI paper.
  ☆43Updated 8 years ago
• lrjconan / deep_parsimonious
  Learning Deep Parsimonious Representations, Deep Learning, Clustering, NIPS 2016
  ☆14Updated 5 years ago
• xternalz / DelugeNets
  DelugeNets: Deep Networks with Efficient and Flexible Cross-layer Information Inflows
  ☆26Updated 8 years ago
• preddy5 / Residual-Learning-and-Stochastic-Depth
  Implementation of Residual Learning with Stochastic Depth http://arxiv.org/pdf/1603.09382v2.pdf
  ☆10Updated 9 years ago
• veronikayurchuk / pretrained-models.pytorch
  Pretrained ConvNets for pytorch: NASNet, ResNeXt, ResNet, InceptionV4, InceptionResnetV2, Xception, DPN, etc.
  ☆77Updated 7 years ago
• HUJI-Deep / Generative-ConvACs
  Experiments from the article "Tensorial Mixture Models"
  ☆25Updated 7 years ago