lee813 / pydpmm

Related projects ⓘ

Alternatives and complementary repositories for pydpmm

• likang7 / variational-dpgmm
  Variational Dirichlet Process Gaussian Mixture Models
  ☆27Updated 9 years ago
• albietz / dpmm
  Variational inference for Dirichlet process mixture models with multinomial mixture components.
  ☆32Updated 10 years ago
• markvdw / GPflow-inter-domain
  Gaussian processes in TensorFlow with modifications to allow inter-domain inducing variables
  ☆13Updated 7 years ago
• CausalRL / DRL
  Deconfounding Reinforcement Learning in Observational Settings
  ☆48Updated 5 years ago
• sjblim / rmsn_nips_2018
  ☆37Updated 5 years ago
• FelixOpolka / Deep-Gaussian-Process
  🤿 Implementation of doubly stochastic deep Gaussian Process using GPflow and TensorFlow 2.0
  ☆26Updated 9 months ago
• JFChi / Dirichlet-Hawkes-Process
  ☆13Updated 6 years ago
• Osier-Yi / SITE
  ☆58Updated 2 years ago
• BjornarVass / Recsys
  ☆21Updated 2 years ago
• xiaoshuai09 / Recurrent-Point-Process
  Modeling the asynchronous event sequence via Recurrent Point Process
  ☆61Updated 6 years ago
• mcusi / tf_dpgmm
  Variational inference in Dirichlet process Gaussian mixture model (tensorflow implementation)
  ☆13Updated 6 years ago
• hongyuanmei / neural-hawkes-particle-smoothing
  Source code of the neural Hawkes particle smoothing (ICML 2019)
  ☆42Updated 5 years ago
• ashudeep / Fair-PGRank
  Code for Policy Learning for Fairness in Ranking paper at NeurIPS 2019
  ☆20Updated 2 years ago
• meowoodie / Learning-Temporal-Point-Processes-via-Reinforcement-Learning
  PPG (Point Process Generator) is a Reinforcement Learning framework that is able to produce actions by imitating expert sequences.
  ☆13Updated 5 years ago
• WeijiaZhang24 / TEDVAE
  Code for TEDVAE, a VAE-based treatment effect estimation algorithm.
  ☆21Updated last year
• blei-lab / ars-reparameterization
  Source code for Naesseth et. al. "Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms" (2017)
  ☆39Updated 7 years ago
• omitakahiro / NeuralNetworkPointProcess
  code for "Fully Neural Network based Model for General Temporal Point Processes"
  ☆60Updated 3 years ago
• cambridge-mlg / sghmc_dgp
  ☆28Updated 5 years ago
• yincheng / GGP
  Code and data for the paper `Bayesian Semi-supervised Learning with Graph Gaussian Processes'
  ☆38Updated 6 years ago
• GitHubLuCheng / LTEE
  Implementation of paper Long-Term Effect Estimation with Surrogate Representation
  ☆12Updated 4 years ago
• rguo12 / network-deconfounder-wsdm20
  Code for the WSDM '20 paper, Learning Individual Causal Effects from Networked Observational Data.
  ☆74Updated 3 years ago
• ignavierng / notears-tensorflow
  Reimplementation of NOTEARS in Tensorflow
  ☆33Updated last year
• rjagerman / wsdm2019-nonstationary
  Non-stationary Off-policy Evaluation
  ☆13Updated 6 years ago
• belaalb / CEVAE-VampPrior
  CEVAE with VampPrior
  ☆11Updated 6 years ago
• Networks-Learning / hdhp.py
  Code for "Hierarchical Dirichlet-Hawkes process: generative model and inference algorithm", WWW 2017
  ☆36Updated 5 years ago
• prasoongoyal / bnp-vae
  ☆11Updated 6 years ago
• xiaoshuai09 / Wasserstein-Learning-For-Point-Process
  learning point processes by means of optimal transport and wasserstein distance
  ☆54Updated 6 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated last year
• usaito / counterfactual-cv
  (ICML2020) “Counterfactual Cross-Validation: Stable Model Selection Procedure for Causal Inference Models’’
  ☆31Updated last year