Alternatives and similar repositories for neural-statistician

Users that are interested in neural-statistician are comparing it to the libraries listed below

• rr-learning / disentanglement_dataset
  ☆78Updated 2 months ago
• jmtomczak / vae_vampprior
  Code for the paper "VAE with a VampPrior", J.M. Tomczak & M. Welling
  ☆228Updated 7 years ago
• iffsid / disentangling-disentanglement
  ☆91Updated 6 years ago
• anirudh9119 / RIMs
  Code for "Recurrent Independent Mechanisms"
  ☆118Updated 3 years ago
• rdevon / cortex
  A machine learning library for PyTorch
  ☆92Updated 2 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• alexalemi / vib_demo
  ☆91Updated 3 years ago
• vlievin / biva-pytorch
  Official PyTorch BIVA implementation (BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling)
  ☆84Updated 2 years ago
• gbaydin / hypergradient-descent
  Hypergradient descent
  ☆149Updated last year
• eifuentes / swae-pytorch
  Implementation of the Sliced Wasserstein Autoencoder using PyTorch
  ☆103Updated 6 years ago
• CW-Huang / NAF
  Experiments for the Neural Autoregressive Flows paper
  ☆124Updated 4 years ago
• nvcuong / variational-continual-learning
  Implementation of the variational continual learning method
  ☆191Updated 6 years ago
• reiinakano / invariant-risk-minimization
  Implementation of Invariant Risk Minimization https://arxiv.org/abs/1907.02893
  ☆89Updated 5 years ago
• haoliuhl / hybrid-discriminative-generative
  Hybrid Discriminative-Generative Training via Contrastive Learning
  ☆75Updated 2 years ago
• rosinality / igebm-pytorch
  Implicit Generation and Generalization in Energy Based Models in PyTorch
  ☆65Updated 6 years ago
• flennerhag / warpgrad
  Meta-Learning with Warped Gradient Descent
  ☆93Updated 4 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
• AMLab-Amsterdam / FNP
  Implementation of the Functional Neural Process models
  ☆43Updated 4 years ago
• riannevdberg / sylvester-flows
  ☆180Updated 6 years ago
• shaohua0116 / MMAML-Classification
  An official PyTorch implementation of “Multimodal Model-Agnostic Meta-Learning via Task-Aware Modulation” (NeurIPS 2019) by Risto Vuorio*…
  ☆139Updated 5 years ago
• kefirski / bdir_vae
  simple implementation of "Improved Variational Inference with Inverse Autoregressive Flow" paper with pytorch
  ☆52Updated 7 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 years ago
• xqding / Importance_Weighted_Autoencoders
  A PyTorch Implementation of the Importance Weighted Autoencoders
  ☆39Updated 6 years ago
• ritheshkumar95 / energy_based_generative_models
  PyTorch code accompanying our paper on Maximum Entropy Generators for Energy-Based Models
  ☆152Updated 5 years ago
• cianeastwood / qedr
  Quantitative evaluation of disentangled representations
  ☆62Updated 7 years ago
• Gordonjo / versa
  Code to reproduce experiments in "Meta-learning probabilistic inference for prediction"
  ☆70Updated 4 years ago
• yatindandi / Disentangled-Sequential-Autoencoder
  Variational Autoencoder for Unsupervised and Disentangled Representation Learning of content and motion features in sequential data (Mand…
  ☆106Updated 6 years ago
• mingzhang-yin / SIVI
  A variational inference method with accurate uncertainty estimation. It uses a new semi-implicit variational family built on neural netwo…
  ☆54Updated 9 months ago
• PolinaKirichenko / flows_ood
  ☆88Updated 3 years ago
• amir-abdi / disentanglement-pytorch
  Disentanglement library for PyTorch
  ☆278Updated 3 years ago