Alternatives and similar repositories for DeepCDE

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

• GAMES-UChile / mogptk
  Multi-Output Gaussian Process Toolkit
  ☆182Updated 6 months ago
• secondmind-labs / GPflux
  Deep GPs built on top of TensorFlow/Keras and GPflow
  ☆127Updated last year
• wesselb / gpar
  Implementation of the Gaussian Process Autoregressive Regression Model
  ☆68Updated 10 months ago
• vinecopulib / pyvinecopulib
  A Python library for vine copula models
  ☆114Updated 3 weeks ago
• GaussianProcessesCambridge / meetup-resources
  Collection of resources from each meetup event
  ☆13Updated 5 years ago
• amzn / orthogonal-additive-gaussian-processes
  Light-weighted code for Orthogonal Additive Gaussian Processes
  ☆43Updated last year
• lee-group-cmu / NNKCDE
  Nearest Neighbor Kernel Conditional Density Estimation
  ☆11Updated 5 years ago
• DanielBok / copulae
  Multivariate data modelling with Copulas in Python
  ☆159Updated 10 months ago
• lee-group-cmu / FlexCode
  Implementation of Flexible Conditional Density Estimator
  ☆25Updated 5 months ago
• lee-group-cmu / RFCDE
  Random Forests for Conditional Density Estimation
  ☆43Updated 4 years ago
• freelunchtheorem / Conditional_Density_Estimation
  Package implementing various parametric and nonparametric methods for conditional density estimation
  ☆197Updated 2 years ago
• pmorenoz / HetMOGP
  Heterogeneous Multi-output Gaussian Processes
  ☆54Updated 5 years ago
• wesselb / neuralprocesses
  A framework for composing Neural Processes in Python
  ☆89Updated 11 months ago
• TyXe-BDL / TyXe
  ☆155Updated 3 years ago
• asnelt / mixedvines
  Python package for canonical vine copula trees with mixed continuous and discrete marginals
  ☆49Updated last year
• pmorenoz / ContinualGP
  Continual Gaussian Processes
  ☆31Updated 2 years ago
• markvdw / RobustGP
  Robust initialisation of inducing points in sparse variational GP regression models.
  ☆33Updated 3 years ago
• TeaPearce / Deep_Learning_Prediction_Intervals
  ICML paper 'High-Quality Prediction Intervals for Deep Learning: A Distribution-Free, Ensembled Approach'
  ☆93Updated 5 years ago
• wesselb / stheno
  Gaussian process modelling in Python
  ☆226Updated 11 months ago
• tgcsaba / GPSig
  Bayesian Learning from Sequential Data using Gaussian Processes with Signature Covariances
  ☆50Updated 2 years ago
• 000Justin000 / torchdiffeq
  Differentiable ODE solvers with full GPU support and O(1)-memory backpropagation.
  ☆63Updated 4 years ago
• vlad17 / runlmc
  Structurally efficient multi-output linearly coregionalized Gaussian Processes: it's tricky, tricky, tricky, tricky, tricky.
  ☆38Updated 2 years ago
• yromano / cqr
  Conformalized Quantile Regression
  ☆296Updated 3 years ago
• Gabriel-p / pythonMCMC
  A list of Python-based MCMC & ABC packages
  ☆123Updated 6 months ago
• anh-tong / signax
  Signax: Signature computation in JAX
  ☆37Updated 10 months ago
• patrick-kidger / signatory
  Differentiable computations of the signature and logsignature transforms, on both CPU and GPU. (ICLR 2021)
  ☆291Updated last year
• YannDubs / Neural-Process-Family
  Code for the Neural Processes website and replication of 4 papers on NPs. Pytorch implementation.
  ☆227Updated last year
• aboustati / dgplib
  Library for Deep Gaussian Processes based on GPflow
  ☆18Updated 5 years ago
• GAA-UAM / scikit-fda
  Functional Data Analysis Python package
  ☆337Updated last month
• SheffieldML / PyDeepGP
  Deep Gaussian Processes in Python
  ☆236Updated 4 years ago