Alternatives and similar repositories for neurips2019_disentanglement_challenge_starter_kit

Users that are interested in neurips2019_disentanglement_challenge_starter_kit are comparing it to the libraries listed below

• lrjconan / RBP
  Recurrent Back Propagation, Back Propagation Through Optimization, ICML 2018
  ☆42Updated 6 years ago
• jacobandreas / tre
  Measuring compositionality in representation learning
  ☆73Updated 6 years ago
• joelouismarino / iterative_inference
  Implementation of iterative inference in deep latent variable models
  ☆43Updated 5 years ago
• aakhundov / tf-attend-infer-repeat
  TensorFlow-based implementation of "Attend, Infer, Repeat" paper (Eslami et al., 2016, arXiv:1603.08575).
  ☆42Updated 7 years ago
• rr-learning / disentanglement_dataset
  ☆78Updated 2 months ago
• jmtomczak / vae_vpflows
  Code in PyTorch for the convex combination linear IAF and the Householder Flow, J.M. Tomczak & M. Welling
  ☆91Updated 8 years ago
• dfdazac / vaesbd
  Variational Autoencoder with Spatial Broadcast Decoder
  ☆35Updated 6 years ago
• miyosuda / scan
  SCAN: Learning Abstract Hierarchical Compositional Visual Concepts
  ☆54Updated 7 years ago
• akosiorek / attend_infer_repeat
  A Tensorfflow implementation of Attend, Infer, Repeat
  ☆81Updated 6 years ago
• sjoerdvansteenkiste / Relational-NEM
  Code for the "Relational Neural Expectation Maximization: Unsupervised Discovery of Objects and their Interactions" paper.
  ☆73Updated 2 years ago
• paruby / DIP-VAE
  An implementation of DIP-VAE from the paper "Variational Inference of Disentangled Latent Concepts from Unlabelled Observations" by Kumar…
  ☆26Updated 7 years ago
• anirudh9119 / RIMs
  Code for "Recurrent Independent Mechanisms"
  ☆118Updated 3 years ago
• dhh1995 / SCL
  PyTorch implementation for The Scattering Compositional Learner (SCL)
  ☆32Updated 5 years ago
• akosiorek / sqair
  Implementation of Sequential Attend, Infer, Repeat (SQAIR)
  ☆97Updated 6 years ago
• KhrulkovV / geometry-score
  ☆117Updated 6 years ago
• clvrai / Generative-Latent-Optimization-Tensorflow
  Tensorflow implementation of Generative Latent Optimization (GLO) proposed by Facebook AI Research
  ☆95Updated 7 years ago
• insperatum / vhe
  The Variational Homoencoder: Learning to learn high capacity generative models from few examples
  ☆34Updated 2 years ago
• sjoerdvansteenkiste / Neural-EM
  Code for the "Neural Expectation Maximization" paper.
  ☆126Updated 2 years ago
• thanard / causal-infogan
  ☆86Updated 6 years ago
• jacobandreas / l3
  Learning with latent language
  ☆51Updated 4 years ago
• haoliuhl / hybrid-discriminative-generative
  Hybrid Discriminative-Generative Training via Contrastive Learning
  ☆75Updated 2 years ago
• ucla-vision / information-dropout
  Implementation of Information Dropout
  ☆39Updated 8 years ago
• vithursant / VAE-Gumbel-Softmax
  An implementation of a Variational-Autoencoder using the Gumbel-Softmax reparametrization trick in TensorFlow (tested on r1.5 CPU and GPU…
  ☆72Updated 7 years ago
• uber-research / loss-change-allocation
  ☆61Updated 2 years ago
• akosiorek / forge
  Basic experiment framework for tensorflow.
  ☆91Updated 4 years ago
• renmengye / meta-optim-public
  Understanding Short-Horizon Bias in Stochastic Meta-Optimization
  ☆37Updated 7 years ago
• bneyshabur / over-parametrization
  Computing various norms/measures on over-parametrized neural networks
  ☆49Updated 6 years ago
• rizar / systematic-generalization-sqoop
  Code for "Systematic Generalization: What Is Required and Can It Be Learned"
  ☆37Updated 6 years ago
• wlwkgus / NoisyNaturalGradient
  Pytorch Implementation of paper "Noisy Natural Gradient as Variational Inference"
  ☆121Updated 6 years ago
• asteroidhouse / self-tuning-networks
  Code for Self-Tuning Networks (ICLR 2019) https://arxiv.org/abs/1903.03088
  ☆53Updated 6 years ago