GuyHacohen / curriculum_learning
Code implementing the experiments described in the paper "On The Power of Curriculum Learning in Training Deep Networks" by Hacohen & Weinshall (ICML 2019)
☆108Updated 4 years ago
Alternatives and similar repositories for curriculum_learning:
Users that are interested in curriculum_learning are comparing it to the libraries listed below
- Code release for Catastrophic Forgetting Meets Negative Transfer: Batch Spectral Shrinkage for Safe Transfer Learning (NeurIPS 2019)☆24Updated 3 years ago
- Official code for the paper "Meta Soft Label Generation for Noisy Labels" accepted at ICPR 2020.☆19Updated 4 years ago
- Meta Label Correction for Noisy Label Learning☆84Updated 2 years ago
- SKD : Self-supervised Knowledge Distillation for Few-shot Learning☆96Updated last year
- PyTorch implementation of the paper "Generalized Cross Entropy Loss for Training Deep Neural Networks with Noisy Labels" in NIPS 2018☆125Updated 5 years ago
- [NeurIPS 2017] [ICML 2019] Code for complementary-label learning☆45Updated last year
- MoPro: Webly Supervised Learning☆87Updated 3 years ago
- [AAAI 2021] Curriculum Labeling: Revisiting Pseudo-Labeling for Semi-Supervised Learning☆137Updated 4 years ago
- Feature-Critic Networks for Heterogeneous Domain Generalisation☆52Updated 5 years ago
- PyTorch implementation of the paper "SuperLoss: A Generic Loss for Robust Curriculum Learning" in NIPS 2020.☆29Updated 4 years ago
- Compressing Representations for Self-Supervised Learning☆78Updated 3 years ago
- SwAV for CIFAR-10, adapted from https://github.com/facebookresearch/swav☆28Updated 3 years ago
- When Does Label Smoothing Help?_pytorch_implementationimp☆126Updated 5 years ago
- Curriculum Learning by Dynamic Instance Hardness (NeurIPS 2020)☆26Updated 3 years ago
- NeurIPS 2019 : Learning to Propagate for Graph Meta-Learning☆36Updated 5 years ago
- SpotTune: Transfer Learning through Adaptive Fine-tuning☆89Updated 5 years ago
- NeurIPS'19: Meta-Weight-Net: Learning an Explicit Mapping For Sample Weighting (Pytorch implementation for noisy labels).☆284Updated 3 years ago
- Code for the paper "Generalizing to Unseen Domains via Adversarial Data Augmentation", NeurIPS 2018☆121Updated 4 years ago
- PyTorch implementation of consistency regularization methods for semi-supervised learning☆78Updated 4 years ago
- [AAAI-2020] Official implementation for "Online Knowledge Distillation with Diverse Peers".☆72Updated last year
- Code release for NeurIPS 2020 paper "Co-Tuning for Transfer Learning"☆40Updated 2 years ago
- Official implementation of paper Gradient Matching for Domain Generalization☆117Updated 3 years ago
- Sinkhorn Label Allocation is a label assignment method for semi-supervised self-training algorithms. The SLA algorithm is described in fu…☆53Updated 3 years ago
- official PyTorch implementation of paper "Continual Meta-Learning with Bayesian Graph Neural Networks" (AAAI2020)☆61Updated 4 years ago
- PyTorch implementation of Self-supervised Contrastive Regularization for DG (SelfReg) [ICCV2021]☆76Updated 2 years ago
- Laplacian Regularized Few Shot Learning☆81Updated 2 years ago
- Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"☆118Updated last year
- PyTorch implementation of CCSA("Unified Deep Supervised Domain Adaptation and Generalization")☆44Updated 6 years ago
- Large-Scale Few-Shot Learning: Knowledge Transfer With Class Hierarchy☆33Updated 5 years ago
- ☆90Updated 2 years ago