Alternatives and similar repositories for PointProcesses

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

• HongtengXu / PoPPy
  A Point Process Toolbox Based on PyTorch
  ☆133Updated 5 years ago
• Networks-Learning / hdhp.py
  Code for "Hierarchical Dirichlet-Hawkes process: generative model and inference algorithm", WWW 2017
  ☆36Updated 6 years ago
• freelunchtheorem / Conditional_Density_Estimation
  Package implementing various parametric and nonparametric methods for conditional density estimation
  ☆196Updated 2 years ago
• Mogeng / IOHMM
  Input Output Hidden Markov Model (IOHMM) in Python
  ☆169Updated last year
• HongtengXu / Hawkes-Process-Toolkit
  A toolbox of Hawkes processes
  ☆115Updated 7 years ago
• slinderman / pyhawkes
  Python framework for inference in Hawkes processes.
  ☆243Updated 2 years ago
• clinicalml / dmm
  Deep Markov Models
  ☆133Updated 6 years ago
• omitakahiro / NeuralNetworkPointProcess
  code for "Fully Neural Network based Model for General Temporal Point Processes"
  ☆62Updated 4 years ago
• stmorse / hawkes
  Python class for generation and parameter estimation of multivariate Hawkes processes
  ☆170Updated 3 weeks ago
• meowoodie / Spatio-Temporal-Point-Process-Simulator
  A Spatio-temporal point process simulator.
  ☆46Updated 2 years ago
• dunan / MultiVariatePointProcess
  ☆77Updated 7 years ago
• canerturkmen / hawkeslib
  fast parameter estimation for simpler Hawkes processes
  ☆70Updated 3 years ago
• bnpy / bnpy
  Bayesian nonparametric machine learning for Python
  ☆228Updated 2 years ago
• xiaoshuai09 / Wasserstein-Learning-For-Point-Process
  learning point processes by means of optimal transport and wasserstein distance
  ☆54Updated 7 years ago
• Networks-Learning / tpprl
  Code and data for "Deep Reinforcement Learning of Marked Temporal Point Processes", NeurIPS 2018
  ☆81Updated 6 years ago
• blei-lab / deconfounder_tutorial
  ☆87Updated 5 years ago
• GoudetOlivier / CGNN
  Replication code for the article "Learning Functional Causal Models with Generative Neural Networks"
  ☆100Updated 6 years ago
• meowoodie / Reinforcement-Learning-of-Spatio-Temporal-Point-Processes
  A general framework for learning spatio-temporal point processes via reinforcement learning
  ☆30Updated 4 years ago
• xiaoshuai09 / Recurrent-Point-Process
  Modeling the asynchronous event sequence via Recurrent Point Process
  ☆60Updated 7 years ago
• clinicalml / structuredinference
  Structured Inference Networks for Nonlinear State Space Models
  ☆273Updated 8 years ago
• blei-lab / variational-smc
  Reference implementation of variational sequential Monte Carlo proposed by Naesseth et al. "Variational Sequential Monte Carlo" (2018)
  ☆65Updated 6 years ago
• musically-ut / tf_rmtpp
  Recurrent Marked Temporal Point Processes
  ☆56Updated 4 years ago
• PGM-Lab / InferPy
  InferPy: Deep Probabilistic Modeling with Tensorflow Made Easy
  ☆148Updated last year
• zalandoresearch / probrnn
  State space modeling with recurrent neural networks
  ☆45Updated 7 years ago
• shchur / ifl-tpp
  Implementation of "Intensity-Free Learning of Temporal Point Processes" (Spotlight @ ICLR 2020)
  ☆86Updated 4 years ago
• rofuyu / exp-trmf-nips16
  Experimental Codes for Temporal Regularized Matrix Factoriztion for High-dimensional Time Series Prediction.
  ☆79Updated 6 years ago
• kasparmartens / NeuralProcesses
  Neural Processes implementation for 1D regression
  ☆64Updated 6 years ago
• babylonhealth / neuralTPPs
  ☆31Updated 2 years ago
• UCL-SML / Doubly-Stochastic-DGP
  Deep Gaussian Processes with Doubly Stochastic Variational Inference
  ☆151Updated 6 years ago
• grobgl / rnnsm
  ☆18Updated 7 years ago