Alternatives and similar repositories for PPMM

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

• a-norcliffe / sonode
  Experiments from the paper "On Second Order Behaviour in Augmented Neural ODEs"
  ☆58Updated 9 months ago
• crisbodnar / ndp
  Official code for the ICLR 2021 paper Neural ODE Processes
  ☆72Updated 3 years ago
• MichaelArbel / MMD-gradient-flow
  ☆12Updated 11 months ago
• bobby-he / bayesian-ntk
  Code to accompany paper 'Bayesian Deep Ensembles via the Neural Tangent Kernel'
  ☆26Updated 4 years ago
• 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
• 000Justin000 / torchdiffeq
  Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
  ☆60Updated 4 years ago
• dimkal89 / rvae
  ☆38Updated 5 years ago
• team-approx-bayes / kpriors
  Code for Knowledge-Adaptation Priors based on the NeurIPS 2021 paper by Khan and Swaroop.
  ☆16Updated 3 years ago
• xinshi-chen / ParticleFlowBayesRule
  Pytorch implementation for "Particle Flow Bayes' Rule"
  ☆14Updated 6 years ago
• piomonti / carefl
  Code for "Causal autoregressive flows" - AISTATS, 2021
  ☆45Updated 4 years ago
• afqueiruga / StatefulOdeNets
  Refining continuous-in-depth neural networks
  ☆41Updated 3 years ago
• vislearn / GIN
  Code for the paper "Disentanglement by Nonlinear ICA with General Incompressible-flow Networks (GIN)" (2020)
  ☆32Updated 3 years ago
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆26Updated last year
• JeremiasKnoblauch / GVIPublic
  Demos for the paper Generalized Variational Inference (Knoblauch, Jewson & Damoulas, 2019)
  ☆20Updated 6 years ago
• thibsej / unbalanced_gromov_wasserstein
  Implementation of the Gromov-Wasserstein distance to the setting of Unbalanced Optimal Transport
  ☆45Updated 2 years ago
• bunnech / gwgan
  Learning Generative Models across Incomparable Spaces (ICML 2019)
  ☆27Updated 5 years ago
• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆36Updated 5 years ago
• LaurenceA / bayesfunc
  ☆15Updated 2 years ago
• GiulsLu / Sinkhorn-Barycenters
  Sinkhorn Barycenters via Frank-Wolfe algorithm
  ☆26Updated 5 years ago
• AmirTag / OT-ICNN
  Learning the optimal transport map via input convex neural neworks
  ☆41Updated 5 years ago
• bunnech / jkonet
  Proximal Optimal Transport Modeling of Population Dynamics (AISTATS 2022)
  ☆20Updated 2 years ago
• franciscovargas / GP_Sinkhorn
  GP Sinkhorn Implementation, paper: https://www.mdpi.com/1099-4300/23/9/1134
  ☆23Updated 3 years ago
• cyz-ai / neural-approx-ss-lfi
  Codes for ICLR 21 paper: Neural Approximate Sufficient Statistics for Implicit Models
  ☆20Updated 3 years ago
• changliu00 / AWGF
  Codes for "Understanding and Accelerating Particle-Based Variational Inference" (ICML-19)
  ☆22Updated 5 years ago
• PetrMokrov / Large-Scale-Wasserstein-Gradient-Flows
  Source code for Large-Scale Wasserstein Gradient Flows (NeurIPS 2021)
  ☆32Updated 3 years ago
• ilkhem / iVAE
  VAEs and nonlinear ICA: a unifying framework
  ☆35Updated 5 years ago
• RuntianZ / doro
  Distributional and Outlier Robust Optimization (ICML 2021)
  ☆27Updated 3 years ago
• sharpenb / Differentiable-DAG-Sampling
  Differentiable DAG Sampling (ICLR 2022)
  ☆37Updated 2 years ago
• activatedgeek / svgd
  PyTorch implementation of Stein Variational Gradient Descent
  ☆45Updated 2 years ago