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
- Code for the ICML 2021 paper "Bridging Multi-Task Learning and Meta-Learning: Towards Efficient Training and Effective Adaptation", Haoxi…☆68Updated 3 years ago
- MAML implementation (tensorflow)☆14Updated 5 years ago
- Tensorflow implementation of "Meta Dropout: Learning to Perturb Latent Features for Generalization" (ICLR 2020)☆27Updated 4 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
- Pytorch implementation of neural processes and variants☆27Updated 8 months ago
- ☆17Updated 2 years ago
- ☆31Updated 2 years ago
- A collection of Gradient-Based Meta-Learning Algorithms with pytorch☆62Updated 5 years ago
- ☆36Updated 4 years ago
- Gradient-based Hyperparameter Optimization Over Long Horizons☆13Updated 3 years ago
- Code to reproduce experiments from 'Does Knowledge Distillation Really Work' a paper which appeared in the 2021 NeurIPS proceedings.☆33Updated last year
- Low-variance and unbiased gradient for backpropagation through categorical random variables, with application in variational auto-encoder…☆17Updated 4 years ago
- Bayesian Attention Modules☆35Updated 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…☆40Updated 4 years ago
- A PyTorch implementation of "Meta-Amortized Variational Inference and Learning" (https://arxiv.org/abs/1902.01950)☆14Updated 5 years ago
- Energy-Based Models for Continual Learning Official Repository (PyTorch)☆41Updated 2 years ago
- ☆64Updated 4 years ago
- Gradient Starvation: A Learning Proclivity in Neural Networks☆61Updated 4 years ago
- ☆27Updated 4 years ago
- Improving Transformation Invariance in Contrastive Representation Learning☆13Updated 4 years ago
- Official PyTorch implementation of "Meta-Calibration: Learning of Model Calibration Using Differentiable Expected Calibration Error"☆34Updated last year
- Low-variance, efficient and unbiased gradient estimation for optimizing models with binary latent variables. (ICLR 2019)☆28Updated 6 years ago
- An Empirical Study of Invariant Risk Minimization☆27Updated 4 years ago
- ☆19Updated 5 years ago
- Sharp-MAML: Sharpness-Aware Model-Agnostic Meta Learning☆30Updated 2 years ago
- ☆38Updated 5 months ago
- Learning To Stop While Learning To Predict☆34Updated 2 years ago
- Official code for ICLR 2020 paper "A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning."☆100Updated 4 years ago