k-r-allen / impLinks
infinite mixture prototypes for few-shot learning
☆51Updated 2 years ago
Alternatives and similar repositories for imp
Users that are interested in imp are comparing it to the libraries listed below
Sorting:
- Chainer Implementation of TapNet: Neural Network Augmented with Task-Adaptive Projection for Few-Shot Learning☆56Updated 5 years ago
- NeurIPS 2019 : Learning to Propagate for Graph Meta-Learning☆36Updated 5 years ago
- Code for Unsupervised Learning via Meta-Learning.☆66Updated 4 years ago
- official PyTorch implementation of paper "Continual Meta-Learning with Bayesian Graph Neural Networks" (AAAI2020)☆63Updated 4 years ago
- Tensorflow implementation of "Learning to Balance: Bayesian Meta-learning for Imbalanced and Out-of-distribution Tasks" (ICLR 2020 oral)☆101Updated 4 years ago
- The implementation of https://papers.nips.cc/paper/7352-tadam-task-dependent-adaptive-metric-for-improved-few-shot-learning . TADAM is a …☆106Updated 2 years ago
- The source code of our ACM MM 2019 paper "TGG: Transferable Graph Generation for Zero-shot and Few-shot Learning".☆25Updated 5 years ago
- Learning to Self-Train for Semi-Supervised Few-Shot☆94Updated 2 years ago
- Code accompanying the ICML-2018 paper "Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace"☆38Updated 6 years ago
- Neat and flexible implementation of MAML in pytorch: https://arxiv.org/abs/1703.03400☆60Updated 3 years ago
- Code for the paper "Selecting Relevant Features from a Universal Representation for Few-shot Classification"☆41Updated 4 years ago
- Feature-Critic Networks for Heterogeneous Domain Generalisation☆53Updated 6 years ago
- Large-Scale Few-Shot Learning: Knowledge Transfer With Class Hierarchy☆33Updated 5 years ago
- IJCAI 2019 : Prototype Propagation Networks (PPN) for Weakly-supervised Few-shot Learning on Category Graph☆55Updated 5 years ago
- Official implementation of "iTAML : An Incremental Task-Agnostic Meta-learning Approach". CVPR 2020☆97Updated last year
- Pytorch Code for ICLR19 paper: Learning to Propagate Labels: Transductive Propagation Network for Few-shot Learning.☆176Updated 3 years ago
- SKD : Self-supervised Knowledge Distillation for Few-shot Learning☆98Updated last year
- Codes for UODTN; Open domain recognition; CVPR19☆45Updated 4 years ago
- ARML for ICLR 2020☆42Updated 5 years ago
- Class Normalization for Continual Zero-Shot Learning☆34Updated 4 years ago
- Transductive Zero-Shot Learning with Visual Structure Constraint, in NeurIPS 2019☆44Updated 5 years ago
- Code for TAFE-Net: Task-Aware Feature Embeddings for Low Shot Learning (CVPR 2019)☆56Updated 5 years ago
- Official Pytorch Implementation for CVPR'20 paper: Deep Semantic Clustering by Partition Confidence Maximisation☆58Updated 4 years ago
- MoPro: Webly Supervised Learning☆87Updated last month
- Attentive Region Embedding Network for Zero-shot Learning (CVPR 2019)☆58Updated 5 years ago
- ☆91Updated 3 years ago
- (NeurIPS 2020) Meta-Consolidation for Continual Learning☆37Updated 4 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
- Pytorch implementation of Meta-Learned Confidence for Few-shot Learning☆71Updated 4 years ago
- Code for the paper "Generalizing to Unseen Domains via Adversarial Data Augmentation", NeurIPS 2018☆121Updated 5 years ago