Alternatives and similar repositories for admm_nn

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

• huangleiBuaa / ONI
  PyTorch and Torch implementation for our accepted CVPR 2020 paper (Oral): Controllable Orthogonalization in Training DNNs
  ☆25Updated 4 years ago
• icml-mcbn / mcbn
  ☆53Updated 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
• MinhyungCho / riemannian-batch-normalization-pytorch
  Riemannian approach to batch normalization
  ☆22Updated 8 years ago
• musikisomorphie / swd
  unsupervised video and image generation
  ☆57Updated 5 years ago
• minhtannguyen / SRSGD
  Code base for SRSGD.
  ☆28Updated 5 years ago
• zs-zhong / D-LADMM
  The code for Differentiable Linearized ADMM (ICML 2019)
  ☆36Updated 6 years ago
• BaoWangMath / EnResNet
  ☆20Updated 6 years ago
• shengliu66 / ConvNorm
  Official Implementation of Convolutional Normalization: Improving Robustness and Training for Deep Neural Networks
  ☆30Updated 3 years ago
• janericlenssen / group_equivariant_capsules_pytorch
  Pytorch implementation of Group Equivariant Capsule Networks
  ☆29Updated 7 years ago
• KaosEngineer / PriorNetworks-OLD
  ☆42Updated 6 years ago
• ricvolpi / domain-shift-robustness
  Code for the paper "Addressing Model Vulnerability to Distributional Shifts over Image Transformation Sets", ICCV 2019
  ☆27Updated 5 years ago
• XiaoxiaSun / supervised-deep-sparse-coding-networks
  supervised deep sparse coding networks
  ☆31Updated 8 years ago
• bpucla / latent-space-EBM-prior
  ☆38Updated 5 years ago
• ermongroup / sparse_gen
  Code for "Modeling Sparse Deviations for Compressed Sensing using Generative Models", ICML 2018
  ☆24Updated 7 years ago
• ColinQiyangLi / LConvNet
  Implementation of Methods Proposed in Preventing Gradient Attenuation in Lipschitz Constrained Convolutional Networks (NeurIPS 2019)
  ☆36Updated 5 years ago
• jh-jeong / selective-convolution
  Code for the paper "Training CNNs with Selective Allocation of Channels" (ICML 2019)
  ☆25Updated 6 years ago
• VITA-Group / Orthogonality-in-CNNs
  [NeurIPS '18] "Can We Gain More from Orthogonality Regularizations in Training Deep CNNs?" Official Implementation.
  ☆130Updated 4 years ago
• microsoft / conservative-uncertainty-estimation-random-priors
  Source code for paper Conservative Uncertainty Estimation By Fitting Prior Networks (ICLR 2020)
  ☆22Updated 3 years ago
• denisyarats / densenet_cifar10
  Meta-learning learning rates with higher
  ☆12Updated 6 years ago
• aditya-grover / uae
  Uncertainty Autoencoders, AISTATS 2019
  ☆56Updated 6 years ago
• huangleiBuaa / IterNorm
  This project is the Torch implementation of our accepted CVPR 2019 paper, Iterative Normalization: Beyond Standardization towards Effic…
  ☆25Updated 4 years ago
• VITA-Group / Once-for-All-Adversarial-Training
  [NeurIPS 2020] "Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free" by Haotao Wang*, Tianlong C…
  ☆44Updated 4 years ago
• jovitalukasik / vs_gae
  ☆10Updated last year
• TUM-DAML / dbu-robustness
  Evaluating Robustness of Predictive Uncertainty Estimation: Are Dirichlet-based Models Reliable ? (ICML 2021)
  ☆28Updated 3 years ago
• human-analysis / pytorchnet
  Generalized Framework for PyTorch
  ☆32Updated 4 years ago
• fjxmlzn / PacGAN
  [NeurIPS 2018] [JSAIT] PacGAN: The power of two samples in generative adversarial networks
  ☆82Updated 5 years ago
• dizam92 / pyTorchReg
  Applied Sparse regularization (L1), Weight decay regularization (L2), ElasticNet, GroupLasso and GroupSparseLasso to Neuronal Network.
  ☆38Updated 3 years ago
• atilberk / evidential-deep-learning-to-quantify-classification-uncertainty
  Work on Evidential Deep Learning to Quantify Classification Uncertainty
  ☆60Updated 7 years ago
• skolouri / swgmm
  Sliced Wasserstein Distance for Learning Gaussian Mixture Models
  ☆66Updated 2 years ago