Alternatives and similar repositories for meta-blocks

Users that are interested in meta-blocks are comparing it to the libraries listed below

• siavash-khodadadeh / MetaLearning-TF2.0
  Meta learning framework with Tensorflow 2.0
  ☆118Updated 2 years ago
• ec6dde01667145e58de60f864e05a4 / CausalOptimizationAnon
  ☆65Updated last year
• Luvata / CS330-Stanford-Deep-Multi-Task-and-Meta-Learning
  My notes and assignment solutions for Stanford CS330 (Fall 2019 & 2020) Deep Multi-Task and Meta Learning
  ☆41Updated 2 years ago
• nke001 / causal_learning_unknown_interventions
  Code for "Neural causal learning from unknown interventions"
  ☆104Updated 5 years ago
• mtsang / interaction_interpretability
  Feature Interaction Interpretability via Interaction Detection
  ☆35Updated 2 years ago
• spiglerg / pyMeta
  Library to manage machine learning problems as `Tasks' and to sample from Task distributions. Includes Tensorflow implementation of impli…
  ☆48Updated 3 years ago
• d909b / cxplain
  Causal Explanation (CXPlain) is a method for explaining the predictions of any machine-learning model.
  ☆132Updated 5 years ago
• shaohua0116 / MMAML-Classification
  An official PyTorch implementation of “Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation” (NeurIPS 2019) by Risto Vuorio*…
  ☆140Updated 5 years ago
• AdrienLE / ANIML
  Reproduction of "Model-Agnostic Meta-Learning" (MAML) and "Reptile".
  ☆192Updated 6 years ago
• authors-1901-10912 / A-Meta-Transfer-Objective-For-Learning-To-Disentangle-Causal-Mechanisms
  Code for "A Meta Transfer Objective For Learning To Disentangle Causal Mechanisms"
  ☆127Updated 6 years ago
• cle-ros / RoutingNetworks
  ☆67Updated 5 years ago
• facebookresearch / LearningToLearn
  Collection of algorithms to learn loss and reward functions via gradient-based bi-level optimization.
  ☆103Updated 4 years ago
• djstrouse / information-bottleneck
  a python implementation of various versions of the information bottleneck, including automated parameter searching
  ☆128Updated 5 years ago
• Mehooz / awesome-representation-learning
  The newest reading list for representation learning
  ☆116Updated 4 years ago
• haebeom-lee / l2b
  Tensorflow implementation of "Learning to Balance: Bayesian Meta-learning for Imbalanced and Out-of-distribution Tasks" (ICLR 2020 oral)
  ☆101Updated 4 years ago
• ZhiningLiu1998 / mesa
  [NeurIPS’20] ⚖️ Build powerful ensemble class-imbalanced learning models via meta-knowledge-powered resampler. | 设计元知识驱动的采样器解决类别不平衡问题
  ☆109Updated last year
• debmandal / RL-Causality
  References at the Intersection of Causality and Reinforcement Learning
  ☆89Updated 5 years ago
• KangchengHou / gntk
  Implementation of Graph Neural Tangent Kernel (NeurIPS 2019)
  ☆105Updated 5 years ago
• FerranAlet / modular-metalearning
  ☆78Updated 4 years ago
• rtanno21609 / AdaptiveNeuralTrees
  Adaptive Neural Trees
  ☆155Updated 6 years ago
• AvivNavon / pareto-hypernetworks
  Official implementation of Learning The Pareto Front With HyperNetworks [ICLR 2021]
  ☆104Updated 3 years ago
• ivannz / mlss2019-bayesian-deep-learning
  MLSS2019 Tutorial on Bayesian Deep Learning
  ☆93Updated 5 years ago
• uber-research / loss-change-allocation
  ☆61Updated 2 years ago
• vuoristo / MMAML
  ☆19Updated 5 years ago
• Gordonjo / versa
  Code to reproduce experiments in "Meta-learning probabilistic inference for prediction"
  ☆69Updated 4 years ago
• huaxiuyao / HSML
  HSML for ICML 2019
  ☆51Updated 6 years ago
• wOOL / DNDT
  Deep Neural Decision Trees
  ☆163Updated 3 years ago
• dtak / tree-regularization-public
  Code for AAAI 2018 accepted paper: "Beyond Sparsity: Tree Regularization of Deep Models for Interpretability"
  ☆79Updated 7 years ago
• changliu00 / causal-semantic-generative-model
  Codes for Causal Semantic Generative model (CSG), the model proposed in "Learning Causal Semantic Representation for Out-of-Distribution …
  ☆74Updated 3 years ago
• xbresson / CE7454_2018
  Deep learning course CE7454, 2018
  ☆79Updated 6 years ago