Alternatives and similar repositories for tpprl

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

• musically-ut / tf_rmtpp
  Recurrent Marked Temporal Point Processes
  ☆56Updated 3 years ago
• hongyuanmei / neural-hawkes-particle-smoothing
  Source code of the neural Hawkes particle smoothing (ICML 2019)
  ☆43Updated 6 years ago
• xiaoshuai09 / Recurrent-Point-Process
  Modeling the asynchronous event sequence via Recurrent Point Process
  ☆61Updated 7 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 / hdhp.py
  Code for "Hierarchical Dirichlet-Hawkes process: generative model and inference algorithm", WWW 2017
  ☆36Updated 6 years ago
• dunan / NeuralPointProcess
  ☆90Updated 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.
  ☆14Updated 6 years ago
• shchur / triangular-tpp
  Implementation of "Fast and Flexible Temporal Point Processes with Triangular Maps" (Oral @ NeurIPS 2020)
  ☆23Updated last year
• omitakahiro / NeuralNetworkPointProcess
  code for "Fully Neural Network based Model for General Temporal Point Processes"
  ☆61Updated 4 years ago
• dunan / MultiVariatePointProcess
  ☆77Updated 7 years ago
• yangalan123 / anhp-andtt
  Codebase for Attentive Neural Hawkes Process (A-NHP) and Attentive Neural Datalog Through Time (A-NDTT)
  ☆58Updated 5 months ago
• woshiyyya / ERPP-RMTPP
  A pytorch implementation of ERPP and RMTPP on ATM maintenance dataset.
  ☆55Updated 5 years ago
• hongyuanmei / tpp-short-course
  A short course on temporal point process and modeling irregular time series
  ☆21Updated 4 years ago
• achab / nphc
  NPHC
  ☆17Updated 4 years ago
• meowoodie / Spatio-Temporal-Point-Process-Simulator
  A Spatio-temporal point process simulator.
  ☆46Updated 2 years ago
• CausalRL / DRL
  Deconfounding Reinforcement Learning in Observational Settings
  ☆51Updated 6 years ago
• sordonia / zforcing
  ZForcing Repo
  ☆40Updated 7 years ago
• HongtengXu / PoPPy
  A Point Process Toolbox Based on PyTorch
  ☆131Updated 4 years ago
• arunvenk / DaD
  Data as Demonstrator (DaD) is a meta learning algorithm to improve the multi-step predictive capabilities of a learned time series (e.g. …
  ☆33Updated 8 years ago
• shchur / ifl-tpp
  Implementation of "Intensity-Free Learning of Temporal Point Processes" (Spotlight @ ICLR 2020)
  ☆85Updated 4 years ago
• YRussac / WeightedLinearBandits
  Code associated with the NeurIPS19 paper "Weighted Linear Bandits in Non-Stationary Environments"
  ☆17Updated 5 years ago
• thjashin / gp-infer-net
  Scalable Training of Inference Networks for Gaussian-Process Models, ICML 2019
  ☆41Updated 2 years ago
• hongyuanmei / neurawkes
  Source code of The Neural Hawkes Process (NIPS 2017)
  ☆223Updated 3 years ago
• meowoodie / Reinforcement-Learning-of-Spatio-Temporal-Point-Processes
  A general framework for learning spatio-temporal point processes via reinforcement learning
  ☆31Updated 4 years ago
• HongtengXu / Hawkes-Process-Toolkit
  A toolbox of Hawkes processes
  ☆113Updated 7 years ago
• MatthewDaws / PointProcesses
  Basics of point processes using python for simulation
  ☆62Updated 7 years ago
• lee813 / pydpmm
  Direct Gibbs sampling for DPMM using python.
  ☆16Updated 8 years ago
• YingzhenLi / VRbound
  code release for the NIPS 2016 paper
  ☆27Updated 8 years ago
• zalandoresearch / probrnn
  State space modeling with recurrent neural networks
  ☆45Updated 7 years ago
• razhangwei / CAUSE
  ☆30Updated 3 years ago