mingzhang-yin / Meta-learning-without-memorization
A study on the following problems: what the memorization problem is in meta-learning; why memorization problem happens; and how we can prevent it. (ICLR 2020)
☆21Updated 2 years ago
Alternatives and similar repositories for Meta-learning-without-memorization:
Users that are interested in Meta-learning-without-memorization are comparing it to the libraries listed below
- ☆30Updated 3 years ago
- ☆14Updated 6 years ago
- Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation", Haoxi…☆68Updated 3 years ago
- This repository contains implementations of the paper, Bayesian Model-Agnostic Meta-Learning.☆60Updated 5 years ago
- Implementation of the models and datasets used in "An Information-theoretic Approach to Distribution Shifts"☆25Updated 3 years ago
- Tensorflow implementation of "Meta Dropout: Learning to Perturb Latent Features for Generalization" (ICLR 2020)☆27Updated 5 years ago
- This repository contains the code used in a publication 'Active Learning for Decision-Making from Imbalanced Observational Data', Iiris S…☆11Updated 5 years ago
- A collection of Gradient-Based Meta-Learning Algorithms with pytorch☆62Updated 5 years ago
- ☆32Updated 2 years ago
- An Empirical Study of Invariant Risk Minimization☆27Updated 4 years ago
- The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) p…☆41Updated 4 years ago
- ☆38Updated 6 months ago
- ☆36Updated 4 years ago
- MAML implementation (tensorflow)☆14Updated 6 years ago
- ARML for ICLR 2020☆42Updated 4 years ago
- ☆20Updated 4 years ago
- ☆64Updated 4 years ago
- Low-variance and unbiased gradient for backpropagation through categorical random variables, with application in variational auto-encoder…☆17Updated 4 years ago
- Official code for ICLR 2020 paper "A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning."☆100Updated 4 years ago
- Learning To Stop While Learning To Predict☆34Updated 2 years ago
- Official PyTorch implementation of "Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error"☆34Updated last year
- ☆17Updated 2 years ago
- ☆65Updated 9 months ago
- ☆27Updated 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
- Towards increasing stability of neural networks for continual learning: https://arxiv.org/abs/2006.06958.pdf (NeurIPS'20)☆75Updated 2 years ago
- Energy-Based Models for Continual Learning Official Repository (PyTorch)☆41Updated 2 years ago
- Code to reproduce experiments from 'Does Knowledge Distillation Really Work' a paper which appeared in the 2021 NeurIPS proceedings.☆33Updated last year
- Official Code Repository for La-MAML: Look-Ahead Meta-Learning for Continual Learning"☆76Updated 4 years ago
- ☆40Updated 5 years ago