Alternatives and similar repositories for Classification-using-KMM-Kernel-Mean-Matching-

Users that are interested in Classification-using-KMM-Kernel-Mean-Matching- are comparing it to the libraries listed below

• vodp / py-kmm
  A Python implementation of Kernel Mean Matching data reweighting algorithm
  ☆32Updated 9 years ago
• nitarshan / bayes-by-backprop
  PyTorch implementation of "Weight Uncertainty in Neural Networks"
  ☆176Updated 3 years ago
• kilianFatras / variance_reduced_neural_networks
  Implementation of SVRG and SAGA optimization algorithms for deep learning topics.
  ☆72Updated 4 years ago
• stevenliuyi / information-bottleneck
  demonstration of the information bottleneck theory for deep learning
  ☆64Updated 7 years ago
• xuanqing94 / BayesianDefense
  Adv-BNN: Improved Adversarial Defense through Robust Bayesian Neural Network
  ☆62Updated 6 years ago
• rflamary / JDOT
  Joint distribution optimal transportation for domain adaptation
  ☆102Updated 7 years ago
• ytsmiling / lmt
  Public code for a paper "Lipschitz-Margin Training: Scalable Certification of Perturbation Invariance for Deep Neural Networks."
  ☆34Updated 6 years ago
• reiinakano / invariant-risk-minimization
  Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893
  ☆89Updated 5 years ago
• alexalemi / vib_demo
  ☆91Updated 3 years ago
• lsgos / uncertainty-adversarial-paper
  Code for the paper 'Understanding Measures of Uncertainty for Adversarial Example Detection'
  ☆61Updated 7 years ago
• duchi-lab / certifiable-distributional-robustness
  Certifying Some Distributional Robustness with Principled Adversarial Training (https://arxiv.org/abs/1710.10571)
  ☆45Updated 7 years ago
• namkoong-lab / robustopt
  ☆43Updated 6 years ago
• lucfra / FAR-HO
  Gradient based hyperparameter optimization & meta-learning package for TensorFlow
  ☆188Updated 5 years ago
• fengliu90 / DK-for-TST
  This is the source code for Learning Deep Kernels for Non-Parametric Two-Sample Tests (ICML2020).
  ☆50Updated 4 years ago
• bneyshabur / path-sgd
  Path-SGD: Path-Normalized Optimization in Deep Neural Networks
  ☆19Updated 6 years ago
• artemyk / ibsgd
  ☆153Updated 5 years ago
• charlesjin / adversarial_regularization
  A method based on manifold regularization for training adversarially robust neural networks
  ☆9Updated 5 years ago
• GiulsLu / OT-gradients
  ☆12Updated 6 years ago
• OscarcarLi / PrototypeDL
  Codebase for "Deep Learning for Case-based Reasoning through Prototypes: A Neural Network that Explains Its Predictions" (to appear in AA…
  ☆75Updated 7 years ago
• BayesWatch / deep-kernel-transfer
  Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)
  ☆205Updated 3 years ago
• ermongroup / ssdkl
  Code that accompanies the paper Semi-supervised Deep Kernel Learning: Regression with Unlabeled Data by Minimizing Predictive Variance
  ☆76Updated 6 years ago
• nhartland / KL-divergence-estimators
  Testing methods for estimating KL-divergence from samples.
  ☆64Updated 4 months ago
• ShinKyuY / Understanding_Black_box_Predictions_via_Influence_Functions_tutorial_MNIST
  Tiny Tutorial on https://arxiv.org/abs/1703.04730
  ☆13Updated 5 years ago
• nvcuong / variational-continual-learning
  Implementation of the variational continual learning method
  ☆191Updated 6 years ago
• avirmaux / lipEstimation
  ☆59Updated 2 years ago
• yaodongyu / Rethink-BiasVariance-Tradeoff
  Rethinking Bias-Variance Trade-off for Generalization of Neural Networks
  ☆49Updated 4 years ago
• facebookresearch / SingleModelUncertainty
  Learning error bars for neural network predictions
  ☆71Updated 5 years ago
• AMLab-Amsterdam / DIVA
  Implementation of 'DIVA: Domain Invariant Variational Autoencoders'
  ☆103Updated 5 years ago
• litian96 / TERM
  Tilted Empirical Risk Minimization (ICLR '21)
  ☆59Updated last year
• yaircarmon / semisup-adv
  Semisupervised learning for adversarial robustness https://arxiv.org/pdf/1905.13736.pdf
  ☆142Updated 5 years ago