yangsenius / learning-to-learn-by-pytorchLinks
"Learning to learn by gradient descent by gradient descent "by PyTorch -- a simple re-implementation.
☆60Updated 5 years ago
Alternatives and similar repositories for learning-to-learn-by-pytorch
Users that are interested in learning-to-learn-by-pytorch are comparing it to the libraries listed below
Sorting:
- Pytorch version of NIPS'16 "Learning to learn by gradient descent by gradient descent"☆67Updated 2 years ago
- ☆155Updated 5 years ago
- Pytorch Implemtation of Meta-Learning with Latent Embedding Optimization☆48Updated 5 years ago
- Neat and flexible implementation of MAML in pytorch: https://arxiv.org/abs/1703.03400☆60Updated 4 years ago
- Code accompanying the ICML-2018 paper "Gradient-Based Meta-Learning with Learned Layerwise Metric and Subspace"☆38Updated 6 years ago
- Neat implementation of Meta-SGD in pytorch: https://arxiv.org/abs/1707.09835☆89Updated 6 years ago
- Learning To Stop While Learning To Predict☆34Updated 2 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
- Code for Unsupervised Learning via Meta-Learning.☆67Updated 4 years ago
- Implementation of [Progressive Neural Networks](https://arxiv.org/abs/1606.04671) using Pytorch Framework☆52Updated 5 years ago
- Towards increasing stability of neural networks for continual learning: https://arxiv.org/abs/2006.06958.pdf (NeurIPS'20)☆75Updated 2 years ago
- Reproduction of "Model-Agnostic Meta-Learning" (MAML) and "Reptile".☆192Updated 6 years ago
- [ICML 2020] Efficient Continuous Pareto Exploration in Multi-Task Learning☆146Updated 4 years ago
- pytorch implementation of Optimization as a Model for Few-shot Learning☆182Updated 2 years ago
- [NeurIPS 2020] "Once-for-All Adversarial Training: In-Situ Tradeoff between Robustness and Accuracy for Free" by Haotao Wang*, Tianlong C…☆44Updated 3 years ago
- Code implementing the experiments described in the paper "On The Power of Curriculum Learning in Training Deep Networks" by Hacohen & Wei…☆114Updated 5 years ago
- This repository contains implementations of the paper, Bayesian Model-Agnostic Meta-Learning.☆60Updated 6 years ago
- The implementation of "Self-Supervised Generalisation with Meta Auxiliary Learning" [NeurIPS 2019].☆177Updated 3 years ago
- an implementation of Deep Variational Informational Bottleneck in pytorch (https://arxiv.org/pdf/1612.00410.pdf)☆33Updated 7 years ago
- Code for NeurIPS 2019 Paper, "L_DMI: An Information-theoretic Noise-robust Loss Function"☆119Updated 2 years ago
- Code for Unsupervised Learning via Meta-Learning.☆122Updated 6 years ago
- Implementation of "A Simple Neural Attentive Meta-Learner" (SNAIL, https://arxiv.org/pdf/1707.03141.pdf) in PyTorch☆148Updated 6 years ago
- ARML for ICLR 2020☆42Updated 5 years ago
- Code for: "Fast and Flexible Multi-Task Classification Using Conditional Neural Adaptive Processes" and "TaskNorm: Rethinking Batch Norma…☆160Updated 4 years ago
- a respectively concise Implemention of Maml in Module way☆30Updated 5 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
- Code for the paper "Generalizing to Unseen Domains via Adversarial Data Augmentation", NeurIPS 2018☆121Updated 5 years ago
- Code release for Transferable Adversarial Training: A General Approach to Adapting Deep Classifiers (ICML2019)☆81Updated 6 years ago
- Pytorch implementation of Deep Variational Information Bottleneck☆200Updated 7 years ago
- Source code for NeurIPS 2020 paper "Meta-Learning with Adaptive Hyperparameters"☆84Updated 3 years ago