Alternatives and similar repositories for Attentive-Neural-Process

Users that are interested in Attentive-Neural-Process are comparing it to the libraries listed below

• cambridge-mlg / convcnp
  Implementation of the Convolutional Conditional Neural Process
  ☆123Updated 4 years ago
• EmilienDupont / neural-processes
  Pytorch implementation of Neural Processes for functions and images
  ☆230Updated 3 years ago
• acids-ircam / pytorch_flows
  Implementation and tutorials of normalizing flows with the novel distributions module
  ☆165Updated 4 years ago
• CW-Huang / NAF
  Experiments for the Neural Autoregressive Flows paper
  ☆124Updated 3 years ago
• riannevdberg / sylvester-flows
  ☆180Updated 5 years ago
• TrentBrick / PyTorchDiscreteFlows
  Discrete Normalizing Flows implemented in PyTorch
  ☆113Updated 3 years ago
• tonyduan / normalizing-flows
  Neural Spline Flow, RealNVP, Autoregressive Flow, 1x1Conv in PyTorch.
  ☆279Updated last year
• vlievin / biva-pytorch
  Official PyTorch BIVA implementation (BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling)
  ☆84Updated 2 years ago
• pclucas14 / iaf-vae
  Pytorch Implementation of OpenAI's "Improved Variational Inference with Inverse Autoregressive Flow"
  ☆82Updated 5 years ago
• bayesiains / nsf
  Code for Neural Spline Flows paper
  ☆271Updated 4 years ago
• nicola-decao / BNAF
  Pytorch implementation of Block Neural Autoregressive Flow
  ☆178Updated 3 years ago
• izmailovpavel / flowgmm
  ☆148Updated 3 years ago
• senya-ashukha / real-nvp-pytorch
  Real NVP PyTorch a Minimal Working Example | Normalizing Flow
  ☆138Updated 4 years ago
• akandykeller / SelfNormalizingFlows
  ☆68Updated 2 years ago
• xqding / Importance_Weighted_Autoencoders
  A PyTorch Implementation of the Importance Weighted Autoencoders
  ☆40Updated 6 years ago
• rosinality / igebm-pytorch
  Implicit Generation and Generalization in Energy Based Models in PyTorch
  ☆65Updated 6 years ago
• makora9143 / pytorch-convcnp
  A PyTorch Implementation of Convolutional Conditional Neural Process.
  ☆50Updated 5 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• geniki / neural-processes
  PyTorch implementation of Neural Processes
  ☆88Updated 6 years ago
• didriknielsen / survae_flows
  Code for paper "SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows"
  ☆287Updated 4 years ago
• cfinlay / ffjord-rnode
  Regularized Neural ODEs (RNODE)
  ☆82Updated 3 years ago
• ex4sperans / variational-inference-with-normalizing-flows
  Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)
  ☆234Updated 6 years ago
• otokonoko8 / implicit-variational-inference
  The collection of recent papers about variational inference
  ☆85Updated 5 years ago
• sajadn / Exemplar-VAE
  Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation
  ☆69Updated 4 years ago
• wgrathwohl / LSD
  Official Release of "Learning the Stein Discrepancy for Training and Evaluating Energy-Based Models without Sampling"
  ☆49Updated 4 years ago
• ssydasheng / FBNN
  Code for "Functional variational Bayesian neural networks" (https://arxiv.org/abs/1903.05779)
  ☆84Updated 4 years ago
• didriknielsen / pixelcnn_flow
  Code for paper "Closing the Dequantization Gap: PixelCNN as a Single-Layer Flow"
  ☆19Updated 4 years ago
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• paultsw / nice_pytorch
  Nonlinear Independent Components Estimation (Dinh et al, 2014) in PyTorch.
  ☆117Updated 6 years ago
• SamsungLabs / semi-supervised-NFs
  Code for the paper Semi-Conditional Normalizing Flows for Semi-Supervised Learning
  ☆27Updated 3 years ago