The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) paper in Pytorch.
☆41Oct 28, 2020Updated 5 years ago
Alternatives and similar repositories for HowToTrainYourMAMLPytorch
Users that are interested in HowToTrainYourMAMLPytorch are comparing it to the libraries listed below
Sorting:
- Meta-learning learning rates with higher☆12Sep 27, 2019Updated 6 years ago
- This is an article about using variational autoencoders for the generation of new data. It contains the code for generating the plots and…☆12Feb 15, 2021Updated 5 years ago
- higher is a pytorch library allowing users to obtain higher order gradients over losses spanning training loops rather than individual tr…☆1,627Mar 25, 2022Updated 3 years ago
- ☆15Updated this week
- Model Agnostic Meta Learning (MAML) implemented in Flax, the neural network library for JAX.☆21Sep 18, 2020Updated 5 years ago
- An Implementation of Model-Agnostic Meta-Learning in PyTorch with Torchmeta☆241Jul 7, 2020Updated 5 years ago
- ☆12Dec 7, 2017Updated 8 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…☆827Dec 5, 2023Updated 2 years ago
- Program that automatically locks the screen when a face is not detected☆14Jun 18, 2013Updated 12 years ago
- Convex potential flows☆85Nov 19, 2021Updated 4 years ago
- ☆126Jun 3, 2024Updated last year
- Implementation of MAML in numpy, deriving gradients and implementing backprop manually☆14Nov 15, 2018Updated 7 years ago
- Diagnosing Vulnerability of Variational Auto-Encoders to Adversarial Attacks☆13Feb 15, 2022Updated 4 years ago
- Statistical adaptive stochastic optimization methods☆32Mar 28, 2020Updated 5 years ago
- Neat implementation of Meta-SGD in pytorch: https://arxiv.org/abs/1707.09835☆91Apr 8, 2019Updated 6 years ago
- Tensorflow implementation and notebooks for Implicit Maximum Likelihood Estimation☆67Apr 1, 2022Updated 3 years ago
- Repo to accompany paper on Meta Learning with Implicit Gradients (NeurIPS 2019)☆60Jan 19, 2020Updated 6 years ago
- Filter Response Normalization tested on better ImageNet baselines.☆35Mar 28, 2020Updated 5 years ago
- Lifelong Learning via Progressive Distillation and Retrospection☆14Apr 2, 2019Updated 6 years ago
- Code for Unbiased Implicit Variational Inference (UIVI)☆15Jan 18, 2019Updated 7 years ago
- Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation☆69Dec 9, 2020Updated 5 years ago
- Introduction to PyTorch Workshop at the AMLD 2019☆31Jun 10, 2019Updated 6 years ago
- Implementation of different variants of Parseval metric☆13Nov 3, 2014Updated 11 years ago
- A collection of extensions and data-loaders for few-shot learning & meta-learning in PyTorch☆2,053Jul 17, 2023Updated 2 years ago
- Pytorch implementation of COIN++ 🍁☆76Jul 13, 2022Updated 3 years ago
- ☆22Dec 3, 2021Updated 4 years ago
- ☆16Jun 12, 2018Updated 7 years ago
- Hessian trace estimation using PyTorch and Hutch++☆20Oct 29, 2020Updated 5 years ago
- ☆22Mar 7, 2021Updated 4 years ago
- A study on the following problems: what the memorization problem is in meta-learning; why memorization problem happens; and how we can pr…☆21Mar 24, 2023Updated 2 years ago
- A collection of meta-learning algorithms in Jax☆24Sep 3, 2022Updated 3 years ago
- This is the code for the EMNLP 2020 paper "An Unsupervised Joint System for Text Generation from Knowledge Graphs and Semantic Parsing".☆26Jul 16, 2021Updated 4 years ago
- PowerBiMIP is an open-source, efficient bilevel mixed-integer programming (BiMIP) solver, with a special focus on applications in power a…☆34Updated this week
- ☆26Jul 3, 2020Updated 5 years ago
- Evaluating Text Representations on Lexical Composition☆24Oct 30, 2019Updated 6 years ago
- Neural Fixed-Point Acceleration for Convex Optimization☆29Oct 6, 2022Updated 3 years ago
- PyTorch implementation of the CVPR 2018 paper Deep Image Prior by Dmitry Ulyanov et. al.☆24Dec 20, 2019Updated 6 years ago
- Code for "Efficient optimization of loops and limits with randomized telescoping sums"☆27May 13, 2019Updated 6 years ago
- Code for the paper: Fully Trainable and Interpretable Non-Local Sparse Models for Image Restoration (ECCV 2020)☆59Oct 2, 2020Updated 5 years ago