Alternatives and similar repositories for MetaDelta

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

• kfzyqin / Research-Softmax-with-Mutual-Information
  Full implementation of the paper "Rethinking Softmax with Cross-Entropy: Neural Network Classifier as Mutual Information Estimator".
  ☆101Updated 5 years ago
• imtiazziko / LaplacianShot
  Laplacian Regularized Few Shot Learning
  ☆84Updated 3 years ago
• nocotan / born_again_neuralnet
  Unofficial pytorch implementation of Born-Again Neural Networks.
  ☆55Updated 4 years ago
• johnnyasd12 / awesome-few-shot-meta-learning
  awesome few shot / meta learning papers
  ☆53Updated 4 years ago
• xjtushujun / Meta-weight-net_class-imbalance
  NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for class imbalance).
  ☆34Updated 6 years ago
• daooshee / Few-Shot-Learning
  ☆69Updated 5 years ago
• RaptorMai / CVPR20_CLVision_challenge
  1'st Place approach for CVPR 2020 Continual Learning Challenge
  ☆46Updated 5 years ago
• tiangeluo / fsl-global
  Few-Shot Learning with Global Class Representations
  ☆74Updated 3 years ago
• sseung0703 / SSKD_SVD
  ☆51Updated 6 years ago
• brjathu / SKD
  SKD : Self-supervised Knowledge Distillation for Few-shot Learning
  ☆101Updated 2 years ago
• littleredxh / HardNegative
  ☆53Updated 4 years ago
• ahmdtaha / knowledge_evolution
  (CVPR-Oral 2021) PyTorch implementation of Knowledge Evolution approach and Split-Nets
  ☆83Updated 4 years ago
• lorenmt / maxl
  The implementation of "Self-Supervised Generalisation with Meta Auxiliary Learning" [NeurIPS 2019].
  ☆177Updated 3 years ago
• szkocot / Adapting-Auxiliary-Losses-Using-Gradient-Similarity
  Implementation "Adapting Auxiliary Losses Using Gradient Similarity" article
  ☆32Updated 6 years ago
• thuml / CoTuning
  Code release for NeurIPS 2020 paper "Co-Tuning for Transfer Learning"
  ☆39Updated 3 years ago
• dvornikita / SUR
  Code for the paper "Selecting Relevant Features from a Universal Representation for Few-shot Classification"
  ☆41Updated 4 years ago
• alldbi / SuperMix
  Pytorch implementation of CVPR2021 paper: SuperMix: Supervising the Mixing Data Augmentation
  ☆92Updated 3 years ago
• cgnorthcutt / confidentlearning-reproduce
  Official data release to reproduce Confident Learning paper results
  ☆41Updated 3 years ago
• bhpfelix / MTLNAS
  [CVPR 2020] MTL-NAS: Task-Agnostic Neural Architecture Search towards General-Purpose Multi-Task Learning
  ☆94Updated 2 years ago
• alexrame / mixmo-pytorch
  Official Pytorch implementation of MixMo framework
  ☆84Updated 4 years ago
• dwang181 / active-mixup
  Code for Active Mixup in 2020 CVPR
  ☆23Updated 3 years ago
• liulu112601 / URT
  ICLR 2021: A Universal Representation Transformer Layer for Few-Shot Image Classification
  ☆105Updated 4 years ago
• bhanML / Masking
  NeurIPS'18: Masking: A New Perspective of Noisy Supervision
  ☆54Updated 6 years ago
• seongmin-kye / MCT
  Pytorch implementation of Meta-Learned Confidence for Few-shot Learning
  ☆71Updated 4 years ago
• xingruiyu / coteaching_plus
  ICML'19 How does Disagreement Help Generalization against Label Corruption?
  ☆89Updated 6 years ago
• bl0 / negative-margin.few-shot
  PyTorch implementation of “Negative Margin Matters: Understanding Margin in Few-shot Classification”
  ☆152Updated 4 years ago
• Newbeeer / L_DMI
  Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"
  ☆119Updated 2 years ago
• mboudiaf / TIM
  (NeurIPS 2020) Transductive Information Maximization for Few-Shot Learning https://arxiv.org/abs/2008.11297
  ☆123Updated 2 years ago
• thuml / TransNorm
  Code release for "Transferable Normalization: Towards Improving Transferability of Deep Neural Networks" (NeurIPS 2019)
  ☆79Updated 4 years ago
• hytseng0509 / DropGrad
  Regularizing Meta-Learning via Gradient Dropout
  ☆53Updated 5 years ago