Topic: metalearning Goto Github
Some thing interesting about metalearning
Some thing interesting about metalearning
metalearning,Meta Ensemble Self-Learning Model with Optimization
User: ajayarunachalam
metalearning,Predict the bugs, features, and questions based on GitHub text data.
User: ankur3107
metalearning,SemiPFL: Personalized Semi-Supervised Federated Learning Framework for Edge Intelligence
User: arvintashakori
Home Page: https://arvintashakori.github.io/SemiPFLProject/
metalearning,Meta learning is a subfield of machine learning where automatic learning algorithms are applied on metadata about machine learning experiments.
User: ashishpatel26
metalearning,Automated Machine Learning with scikit-learn
Organization: automl
Home Page: https://automl.github.io/auto-sklearn
metalearning,Source Code of "Multi-Objective Meta Learning" [NeurIPS 2021]
User: baijiong-lin
metalearning,🔥[IEEE TPAMI 2023] Official repository TPAMI 2023 paper "Exploiting Field Dependencies for Learning on Categorical Data"
Organization: csiro-robotics
Home Page: https://arxiv.org/abs/2307.09321
metalearning,DropClass and DropAdapt - repository for the paper accepted to Speaker Odyssey 2020
User: cvqluu
metalearning,A toy project on a Automated Machine Learning technique called linear meta learning
User: dijin1000
metalearning,Faster and elegant TensorFlow Implementation of paper: Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks
User: dragen1860
metalearning,MetaTS | Time Series Forecasting using Meta Learning
User: drsasanbarak
Home Page: https://drsasanbarak.github.io/metats
metalearning,Taking causal inference to the extreme!
User: dscolby
Home Page: https://dscolby.github.io/CausalELM.jl/
metalearning,Python Meta-Feature Extractor package.
User: ealcobaca
Home Page: https://pymfe.readthedocs.io
metalearning,Model-Agnostic Meta-Learning for HDR Image Reconstruction. By learning the common structure between all LDR-to-HDR conversion tasks, our model is able to adapt it's predictions given extra exposures of a scene. This novel approach reframes LDR-to-HDR conversion as a meta-learning problem.
User: edwin-pan
metalearning,PyTorch implementation of HyperNetworks (Ha et al., ICLR 2017) for ResNet (Residual Networks)
User: g1910
metalearning,A PyTorch implementation of OpenAI's REPTILE algorithm
User: gabrielhuang
metalearning,autoEnsemble : An AutoML Algorithm for Building Homogeneous and Heterogeneous Stacked Ensemble Models by Searching for Diverse Base-Learners
User: haghish
metalearning,Tensorflow implementation of Synthetic Gradient for RNN (LSTM)
User: hannw
Home Page: https://hannw.github.io/posts/synthetic-gradient-rnn
metalearning,Personalizing Dialogue Agents via Meta-Learning
Organization: hltchkust
metalearning,Skin lesion image analysis that draws on meta-learning to improve performance in the low data and imbalanced data regimes.
User: karthik-d
metalearning,Code for the NeurIPS19 paper "Meta-Learning Representations for Continual Learning"
User: khurramjaved96
Home Page: https://arxiv.org/abs/1905.12588
metalearning,Meta-Learning with Differentiable Convex Optimization (CVPR 2019 Oral)
User: kjunelee
metalearning,A PyTorch Library for Meta-learning Research
Organization: learnables
Home Page: http://learn2learn.net
metalearning,Master's Project
User: lschlessinger1
metalearning,The Contextual Meta-Bandit (CMB) can be used to select models using the context with online learning based on Reiforcement Learning problem. It's can be used for recommender system ensemble, A/B test, and other dynamic model selector problem.
User: marlesson
metalearning,Implementation of "Model-Agnostic Meta-Learning for Fast Adaptation of Deep Networks"
User: martinkersner
metalearning,Latency Estimation for Neural Network Architecture
User: meowpunch
metalearning,This repository contains the implementation for the paper - Exploration via Hierarchical Meta Reinforcement Learning.
User: navneet-nmk
metalearning,Code Repository for "Neural networks embrace diversity" paper
Organization: nonlinearartificialintelligencelab
metalearning,Jax implementation of metalearning diversity paper
Organization: nonlinearartificialintelligencelab
Home Page: https://nonlinearartificialintelligencelab.github.io/jaxDiversity/
metalearning,Attacking on Meta Reinforcement Learning in Pytorch
User: panshark
metalearning,Source code for Self-Adaptive Driving in Nonstationary Environments through Conjectural Online Lookahead Adaptation
User: panshark
metalearning,Pseudocode Implementation of DAML, Domain Adaptive Dialog Generation via Meta Learning
User: qasimwani
Home Page: https://arxiv.org/pdf/1906.03520.pdf
metalearning,Meta-learning by applying MAML to an inner variational auto-encoder to automatically learn generative models with few examples
User: robinka
metalearning,Experiments on GPT-3's ability to fit numerical models in-context.
User: rovle
metalearning,Implementation of SNAIL(A Simple Neural Attentive Meta-Learner) with Gluon
User: seujung
metalearning,This project contains the code for the paper accepted at NeurIPS 2020 - Robust Meta-learning for Mixed Linear Regression with Small Batches.
Organization: sewoonglab
metalearning,Meta learning for few-shot learning task on miniImagenet, using ResNet-18 as a feature extractor. Project for CMPT 726
User: sirandou
metalearning,Code for the research paper Meta-learning with hierarchical models based on similarity of causal mechanisms
User: sophiewharrie
metalearning,
User: srikarym
metalearning,Implementation of Jump-Start Reinforcement Learning (JSRL) with Stable Baselines3
User: steventango
Home Page: https://pypi.org/project/jsrl/
metalearning, A curated list of Meta Learning papers, code, books, blogs, videos, datasets and other resources.
User: sudharsan13296
metalearning,Learning to Learn using One-Shot Learning, MAML, Reptile, Meta-SGD and more with Tensorflow
User: sudharsan13296
metalearning,scPoli legacy code for reproducibility
Organization: theislab
metalearning,MAML implementation in PyTorch.
User: xoriieinpottn
metalearning,Generalizing to New Physical Systems via Context-Informed Dynamics Model
User: yuan-yin
metalearning,Paper: Task-Adaptive Meta-Learning Framework for Advancing Spatial Generalizability.
User: zhexiongliu
Home Page: https://ojs.aaai.org/index.php/AAAI/article/view/26680
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