ashishpatel26 / Meta-Learning-
Meta learning is a subfield of machine learning where automatic learning algorithms are applied on metadata about machine learning experiments.
☆27Updated 5 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:
- 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
- A PyTorch reimplementation of MAML, replicating some of the experiments from the paper.☆41Updated 6 years ago
- Official Code Repository for La-MAML: Look-Ahead Meta-Learning for Continual Learning"☆76Updated 4 years ago
- Energy-Based Models for Continual Learning Official Repository (PyTorch)☆41Updated 2 years ago
- Code for "Supermasks in Superposition"☆123Updated last year
- Pytorch implementation for "The Surprising Positive Knowledge Transfer in Continual 3D Object Shape Reconstruction"☆33Updated 2 years ago
- A collection of Gradient-Based Meta-Learning Algorithms with pytorch☆62Updated 5 years ago
- Codebase for "Online Fast Adaptation and Knowledge Accumulation: a New Approach to Continual Learning". This is a ServiceNow Research pro…☆105Updated 2 years ago
- https://cs330.stanford.edu/☆62Updated 2 years ago
- Original PyTorch implementation of Uncertainty-guided Continual Learning with Bayesian Neural Networks, ICLR 2020☆74Updated 3 years ago
- Notebook for comprehensive analysis of authors, organizations, and countries of ICML 2020 papers.☆56Updated 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…☆21Updated 2 years ago
- A repository to keep track of literature on catastrophic forgetting☆37Updated 5 years ago
- Official code for ICLR 2020 paper "A Neural Dirichlet Process Mixture Model for Task-Free Continual Learning."☆100Updated 4 years ago
- ContinualAI Wiki: a collaborative wiki on Continual/Lifelong Machine Learning☆49Updated 2 years ago
- Explaining a black-box using Deep Variational Information Bottleneck Approach☆46Updated 2 years ago
- Library to manage machine learning problems as `Tasks' and to sample from Task distributions. Includes Tensorflow implementation of impli…☆48Updated 3 years ago
- ☆45Updated 4 years ago
- Official implementation for Likelihood Regret: An Out-of-Distribution Detection Score For Variational Auto-encoder at NeurIPS 2020☆49Updated 4 years ago
- Using / reproducing ACD from the paper "Hierarchical interpretations for neural network predictions" 🧠 (ICLR 2019)☆128Updated 3 years ago
- Implementation of MAML in numpy, deriving gradients and implementing backprop manually☆14Updated 6 years ago
- ☆53Updated 5 years ago
- Implementation of the variational continual learning method☆189Updated 6 years ago
- My notes and assignment solutions for Stanford CS330 (Fall 2019 & 2020) Deep Multi-Task and Meta Learning☆41Updated 2 years ago
- An Empirical Study of Invariant Risk Minimization☆27Updated 4 years ago
- Code for using CDEP from the paper "Interpretations are useful: penalizing explanations to align neural networks with prior knowledge" ht…☆127Updated 4 years ago
- Model Patching: Closing the Subgroup Performance Gap with Data Augmentation☆42Updated 4 years ago
- ☆32Updated 2 years ago
- MODALS: Modality-agnostic Automated Data Augmentation in the Latent Space☆41Updated 4 years ago
- ICLR 2021, Fair Mixup: Fairness via Interpolation☆56Updated 3 years ago