ashishpatel26 / Meta-Learning-Links
Meta learning is a subfield of machine learning where automatic learning algorithms are applied on metadata about machine learning experiments.
☆29Updated 6 years ago
Alternatives and similar repositories for Meta-Learning-
Users that are interested in Meta-Learning- are comparing it to the libraries listed below
Sorting:
- https://cs330.stanford.edu/☆62Updated 2 years ago
- My notes and assignment solutions for Stanford CS330 (Fall 2019 & 2020) Deep Multi-Task and Meta Learning☆41Updated 2 years ago
- Implementations of many meta-learning algorithms to solve the few-shot learning problem in Pytorch☆249Updated 3 years ago
- Code for "Supermasks in Superposition"☆124Updated last year
- Codebase for "Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning". This is a ServiceNow Research pro…☆105Updated 3 years ago
- Official Code Repository for La-MAML: Look-Ahead Meta-Learning for Continual Learning"☆77Updated 4 years ago
- An Implementation of Model-Agnostic Meta-Learning in PyTorch with Torchmeta☆237Updated 5 years ago
- Meta learning framework with Tensorflow 2.0☆118Updated 2 years ago
- MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space☆41Updated 4 years ago
- A list of papers on Active Learning and Uncertainty Estimation for Neural Networks.☆66Updated 5 years ago
- Official code for the paper "Task2Vec: Task Embedding for Meta-Learning" (https://arxiv.org/abs/1902.03545, ICCV 2019)☆123Updated 2 years ago
- A collection of Gradient-Based Meta-Learning Algorithms with pytorch☆64Updated 5 years ago
- Toolkit for building machine learning models that generalize to unseen domains and are robust to privacy and other attacks.☆175Updated last year
- Official code for ICLR 2020 paper "A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning."☆100Updated 5 years ago
- A PyTorch reimplementation of MAML, replicating some of the experiments from the paper.☆42Updated 7 years ago
- Benchmark for Lifelong learning research☆118Updated 4 years ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆129Updated 4 years ago
- ContinualAI Wiki: a collaborative wiki on Continual/Lifelong Machine Learning☆48Updated 3 years ago
- A pytorch implementation of MCDO(Monte-Carlo Dropout methods)☆57Updated 6 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
- The original code for the paper "Benchmarks for Continual Few-Shot Learning".☆35Updated 5 years ago
- Code for the paper "Calibrating Deep Neural Networks using Focal Loss"☆161Updated last year
- PyTorch code corresponding to my blog series on adversarial examples and (confidence-calibrated) adversarial training.☆67Updated 2 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…☆21Updated 2 years ago
- ☆96Updated 4 years ago
- Code for the NeurIPS19 paper "Meta-Learning Representations for Continual Learning"☆204Updated last year
- Implementation for the paper "Adversarial Continual Learning" in PyTorch.☆254Updated 2 years ago
- Sharp-MAML: Sharpness-Aware Model-Agnostic Meta Learning☆33Updated 2 years ago
- Elastic weight consolidation technique for incremental learning.☆148Updated 4 years ago
- A list of papers, blogs, datasets and software in the field of lifelong/continual machine learning☆292Updated 4 years ago