YannDubs / Neural-Process-Family

Related projects ⓘ

Alternatives and complementary repositories for Neural-Process-Family

• EmilienDupont / neural-processes
  Pytorch implementation of Neural Processes for functions and images
  ☆225Updated 2 years ago
• cambridge-mlg / convcnp
  Implementation of the Convolutional Conditional Neural Process
  ☆121Updated 3 years ago
• wesselb / neuralprocesses
  A framework for composing Neural Processes in Python
  ☆78Updated 5 months ago
• soobinseo / Attentive-Neural-Process
  A Pytorch Implementation of Attentive Neural Process
  ☆73Updated 5 years ago
• johannbrehmer / manifold-flow
  Manifold-learning flows (ℳ-flows)
  ☆230Updated 4 years ago
• TeaPearce / Bayesian_NN_Ensembles
  AISTATS paper 'Uncertainty in Neural Networks: Approximately Bayesian Ensembling'
  ☆86Updated 4 years ago
• gpapamak / maf
  Masked Autoregressive Flow
  ☆204Updated 3 months ago
• wassname / attentive-neural-processes
  implementing "recurrent attentive neural processes" to forecast power usage (w. LSTM baseline, MCDropout)
  ☆90Updated 8 months ago
• izmailovpavel / understandingbdl
  ☆235Updated last year
• LukasRinder / normalizing-flows
  Implementation of normalizing flows in TensorFlow 2 including a small tutorial.
  ☆144Updated 2 months ago
• ex4sperans / variational-inference-with-normalizing-flows
  Reimplementation of Variational Inference with Normalizing Flows (https://arxiv.org/abs/1505.05770)
  ☆228Updated 6 years ago
• tonyduan / normalizing-flows
  Neural Spline Flow, RealNVP, Autoregressive Flow, 1x1Conv in PyTorch.
  ☆272Updated 11 months ago
• automl / TransformersCanDoBayesianInference
  Official Implementation of "Transformers Can Do Bayesian Inference", the PFN paper
  ☆187Updated 3 weeks ago
• bayesiains / nsf
  Code for Neural Spline Flows paper
  ☆259Updated 4 years ago
• didriknielsen / survae_flows
  Code for paper "SurVAE Flows: Surjections to Bridge the Gap between VAEs and Flows"
  ☆284Updated 3 years ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆71Updated 2 years ago
• TrentBrick / PyTorchDiscreteFlows
  Discrete Normalizing Flows implemented in PyTorch
  ☆107Updated 3 years ago
• BayesWatch / deep-kernel-transfer
  Official pytorch implementation of the paper "Bayesian Meta-Learning for the Few-Shot Setting via Deep Kernels" (NeurIPS 2020)
  ☆201Updated 2 years ago
• ratschlab / GP-VAE
  TensorFlow implementation for the GP-VAE model described in https://arxiv.org/abs/1907.04155
  ☆127Updated last year
• alisiahkoohi / Langevin-dynamics
  Sampling with gradient-based Markov Chain Monte Carlo approaches
  ☆89Updated 7 months ago
• ratschlab / bnn_priors
  Code for the paper "Bayesian Neural Network Priors Revisited"
  ☆55Updated 3 years ago
• TyXe-BDL / TyXe
  ☆145Updated 2 years ago
• VectorInstitute / vbll
  Simple (and cheap!) neural network uncertainty estimation
  ☆55Updated 2 months ago
• acids-ircam / pytorch_flows
  Implementation and tutorials of normalizing flows with the novel distributions module
  ☆160Updated 4 years ago
• BorealisAI / continuous-time-flow-process
  PyTorch code of "Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows" (NeurIPS 2020)
  ☆47Updated 4 years ago
• AdamCobb / hamiltorch
  PyTorch-based library for Riemannian Manifold Hamiltonian Monte Carlo (RMHMC) and inference in Bayesian neural networks
  ☆425Updated 2 months ago
• patrick-kidger / torchcde
  Differentiable controlled differential equation solvers for PyTorch with GPU support and memory-efficient adjoint backpropagation.
  ☆421Updated last year
• jmaronas / TGP.pytorch
  Repository for the work Transforming Gaussian Processes with Normalizing Flows published at AISTATS 2021
  ☆23Updated last year
• freelunchtheorem / Conditional_Density_Estimation
  Package implementing various parametric and nonparametric methods for conditional density estimation
  ☆187Updated last year
• riannevdberg / sylvester-flows
  ☆178Updated 5 years ago