Alternatives and similar repositories for constrained_sparsity:

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

• f-dangel / curvlinops
  PyTorch linear operators for curvature matrices (Hessian, Fisher/GGN, KFAC, ...)
  ☆24Updated this week
• singlasahil14 / SOC
  Code for the ICML 2021 and ICLR 2022 papers: Skew Orthogonal Convolutions, Improved deterministic l2 robustness on CIFAR-10 and CIFAR-100
  ☆18Updated 2 years ago
• chenlin9 / Gaussianization_Flows
  ☆22Updated 4 years ago
• f-dangel / singd
  [ICML 2024] SINGD: KFAC-like Structured Inverse-Free Natural Gradient Descent (http://arxiv.org/abs/2312.05705)
  ☆21Updated 2 months ago
• locuslab / orthogonal-convolutions
  Implementations of orthogonal and semi-orthogonal convolutions in the Fourier domain with applications to adversarial robustness
  ☆43Updated 3 years ago
• blaisedelattre / lip4conv
  Code for Spectral Norm of Convolutional Layers with Circular and Zero Paddings and Efficient Bound of Lipschitz Constant for Convolutiona…
  ☆14Updated 11 months ago
• gortizji / linearized-networks
  Source code of "What can linearized neural networks actually say about generalization?
  ☆19Updated 3 years ago
• Typal-Research / jacobian_free_backprop
  Implicit networks can be trained efficiently and simply by using Jacobian-free Backprop (JFB).
  ☆35Updated 3 years ago
• LaurenceA / bayesfunc
  ☆15Updated 2 years ago
• hushon / JAX-ResNet-CIFAR10
  Simple CIFAR10 ResNet example with JAX.
  ☆22Updated 3 years ago
• runame / laplace-refinement
  Posterior Refinement Improves Sample Efficiency in Bayesian Neural Networks
  ☆9Updated 2 years ago
• jongharyu / neural-svd
  ☆15Updated 4 months ago
• ernoult / scalingDTP
  "Towards Scaling Difference Target Propagation by Learning Backprop Targets" (ICML 2022)
  ☆11Updated 2 years ago
• locuslab / edge-of-stability
  ☆63Updated last month
• ehoogeboom / convolution_exponential_and_sylvester
  ☆28Updated 2 years ago
• juntang-zhuang / TorchDiffEqPack
  ☆45Updated last year
• cbg-ethz / bmi
  Mutual information estimators and benchmark
  ☆39Updated this week
• tudor-berariu / fisher-information-matrix
  PyTorch implementation of FIM and empirical FIM
  ☆58Updated 6 years ago
• meulemansalex / theoretical_framework_for_target_propagation
  Python implementation of the methods in Meulemans et al. 2020 - A Theoretical Framework For Target Propagation
  ☆30Updated 2 months ago
• pnnl / torchntk
  ☆26Updated last year
• FrederikWarburg / LaplaceAE
  ☆32Updated 2 years ago
• TimRoith / BregmanLearning
  Optimizing neural networks via an inverse scale space flow.
  ☆16Updated 11 months ago
• fKunstner / noise-sgd-adam-sign
  ☆15Updated last year
• streethagore / ForwardLocalGradient
  This is the official implementation of the ICML 2023 paper - Can Forward Gradient Match Backpropagation ?
  ☆12Updated last year
• tranbahien / you-need-a-good-prior
  All You Need is a Good Functional Prior for Bayesian Deep Learning (JMLR 2022)
  ☆21Updated 2 years ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆27Updated 3 years ago
• gpauloski / kfac-pytorch
  Distributed K-FAC Preconditioner for PyTorch
  ☆84Updated this week
• IlanPrice / DCTpS
  Code for testing DCT plus Sparse (DCTpS) networks
  ☆14Updated 3 years ago
• AlexanderMath / fasth
  Code for the article "What if Neural Networks had SVDs?", to be presented as a spotlight paper at NeurIPS 2020.
  ☆72Updated 5 months ago
• lzhangbv / eva
  [ICLR 2023] Eva: Practical Second-order Optimization with Kronecker-vectorized Approximation
  ☆12Updated last year