Alternatives and similar repositories for snp

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

• soobinseo / Attentive-Neural-Process
  A Pytorch Implementation of Attentive Neural Process
  ☆75Updated 6 years ago
• yoonholee / pytorch-vae
  A minimal pytorch implementation of VAE, IWAE, MIWAE
  ☆47Updated 2 years ago
• AMLab-Amsterdam / FNP
  Implementation of the Functional Neural Process models
  ☆43Updated 5 years ago
• sungyubkim / amortized_svgd
  A pytorch implementation of Amortized Stein Variational Gradient Descent/ Stein GAN
  ☆19Updated 6 years ago
• sajadn / Exemplar-VAE
  Exemplar VAE: Linking Generative Models, Nearest Neighbor Retrieval, and Data Augmentation
  ☆69Updated 4 years ago
• vsimkus / torch-reparametrised-mixture-distribution
  PyTorch implementation of the mixture distribution family with implicit reparametrisation gradients.
  ☆19Updated last year
• cunningham-lab / igr
  ☆30Updated 4 years ago
• dfdazac / vaesbd
  Variational Autoencoder with Spatial Broadcast Decoder
  ☆35Updated 6 years ago
• tung-nd / TNP-pytorch
  Official implementation of Transformer Neural Processes
  ☆78Updated 2 years ago
• makora9143 / pytorch-convcnp
  A PyTorch Implementation of Convolutional Conditional Neural Process.
  ☆51Updated 5 years ago
• juntang-zhuang / torch_ACA
  repo for paper: Adaptive Checkpoint Adjoint (ACA) method for gradient estimation in neural ODE
  ☆56Updated 4 years ago
• phlippe / CITRIS
  Code repository of the paper "CITRIS: Causal Identifiability from Temporal Intervened Sequences" and "iCITRIS: Causal Representation Lear…
  ☆53Updated 2 years ago
• MichaelArbel / GeneralizedEBM
  ☆54Updated last year
• anirudh9119 / RIMs
  Code for "Recurrent Independent Mechanisms"
  ☆118Updated 3 years ago
• cambridge-mlg / convcnp
  Implementation of the Convolutional Conditional Neural Process
  ☆124Updated 4 years ago
• juho-lee / bnp
  Pytorch implementation of neural processes and variants
  ☆29Updated last year
• team-approx-bayes / dnn2gp
  Approximate Inference Turns Deep Networks into Gaussian Processes (dnn2gp)
  ☆48Updated 5 years ago
• BorealisAI / continuous-time-flow-process
  PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)
  ☆48Updated 4 years ago
• cagatayyildiz / ODE2VAE
  ODE2VAE: Deep generative second order ODEs with Bayesian neural networks
  ☆129Updated 11 months ago
• vlievin / biva-pytorch
  Official PyTorch BIVA implementation (BIVA: A Very Deep Hierarchy of Latent Variables for Generative Modeling)
  ☆84Updated 2 years ago
• facebookresearch / neural_stpp
  Deep generative modeling for time-stamped heterogeneous data, enabling high-fidelity models for a large variety of spatio-temporal domain…
  ☆105Updated 3 years ago
• bamos / HowToTrainYourMAMLPytorch
  The original code for the paper "How to train your MAML" along with a replication of the original "Model Agnostic Meta Learning" (MAML) p…
  ☆41Updated 4 years ago
• FerranAlet / modular-metalearning
  ☆78Updated 4 years ago
• ermongroup / f-dre
  Featurized Density Ratio Estimation
  ☆20Updated 4 years ago
• microsoft / deterministic-variational-inference
  Sample code for running deterministic variational inference to train Bayesian neural networks
  ☆100Updated 6 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆73Updated 3 years ago
• a-norcliffe / sonode
  Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"
  ☆58Updated 10 months ago
• guxd / deepHMM
  A PyTorch implementation of a Deep Hidden Markov Model [Structured Inference Networks for Nonlinear State Space Models]
  ☆57Updated last year
• IBM / OoD
  Repository for theory and methods for Out-of-Distribution (OoD) generalization
  ☆63Updated 3 years ago
• EmilienDupont / neural-processes
  Pytorch implementation of Neural Processes for functions and images
  ☆232Updated 3 years ago