Alternatives and similar repositories for tpp-short-course:

Users that are interested in tpp-short-course are comparing it to the libraries listed below

• hongyuanmei / neural-hawkes-particle-smoothing
  Source code of the neural Hawkes particle smoothing (ICML 2019)
  ☆43Updated 5 years ago
• hongyuanmei / nce-mpp
  Source code for Noise-Contrastive Estimation for Multivariate Point Processes (NeurIPS 2020).
  ☆15Updated 4 years ago
• xiaoshuai09 / Wasserstein-Learning-For-Point-Process
  learning point processes by means of optimal transport and wasserstein distance
  ☆54Updated 7 years ago
• shchur / triangular-tpp
  Implementation of "Fast and Flexible Temporal Point Processes with Triangular Maps" (Oral @ NeurIPS 2020)
  ☆23Updated last year
• xiaoshuai09 / Recurrent-Point-Process
  Modeling the asynchronous event sequence via Recurrent Point Process
  ☆61Updated 7 years ago
• mtsang / interaction_interpretability
  Feature Interaction Interpretability via Interaction Detection
  ☆34Updated last year
• yangalan123 / anhp-andtt
  Codebase for Attentive Neural Hawkes Process (A-NHP) and Attentive Neural Datalog Through Time (A-NDTT)
  ☆57Updated 2 months ago
• JeanKaddour / SIN
  Causal Effect Inference for Structured Treatments (SIN) (NeurIPS 2021)
  ☆42Updated 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
• musically-ut / tf_rmtpp
  Recurrent Marked Temporal Point Processes
  ☆56Updated 3 years ago
• seedatnabeel / TE-CDE
  Continuous-Time Modeling of Counterfactual Outcomes Using Neural Controlled Differential Equations (ICML 2022)
  ☆27Updated 2 years ago
• grobgl / rnnsm
  ☆18Updated 7 years ago
• belaalb / CEVAE-VampPrior
  CEVAE with VampPrior
  ☆11Updated 6 years ago
• xiao03 / nh
  A PyTorch Implementation of Neural Hawkes Process. Redefined.
  ☆32Updated 4 years ago
• OATML / ucate
  Uncertainty in Conditional Average Treatment Effect Estimation
  ☆29Updated 3 years ago
• babylonhealth / neuralTPPs
  ☆29Updated last year
• dunan / MultiVariatePointProcess
  ☆77Updated 7 years ago
• BjornarVass / Recsys
  ☆22Updated 2 years ago
• sidak / context-mover-distance-and-barycenters
  Code accompanying our paper at AISTATS 2020
  ☆21Updated 4 years ago
• shchur / ifl-tpp
  Implementation of "Intensity-Free Learning of Temporal Point Processes" (Spotlight @ ICLR 2020)
  ☆84Updated 4 years ago
• d909b / ame
  🤖🤖 Attentive Mixtures of Experts (AMEs) are neural network models that learn to output both accurate predictions and estimates of featu…
  ☆41Updated last year
• csinva / mdl-complexity
  MDL Complexity computations and experiments from the paper "Revisiting complexity and the bias-variance tradeoff".
  ☆18Updated last year
• kingofspace0wzz / wae-rnf-lm
  Pytorch Implemetation for our NAACL2019 Paper "Riemannian Normalizing Flow on Variational Wasserstein Autoencoder for Text Modeling" http…
  ☆62Updated 4 years ago
• HongtengXu / PoPPy
  A Point Process Toolbox Based on PyTorch
  ☆130Updated 4 years ago
• Networks-Learning / tpprl
  Code and data for "Deep Reinforcement Learning of Marked Temporal Point Processes", NeurIPS 2018
  ☆77Updated 5 years ago
• dalab / matrix-manifolds
  Source code for the "Computationally Tractable Riemannian Manifolds for Graph Embeddings" paper
  ☆35Updated 4 years ago
• dunan / NeuralPointProcess
  ☆89Updated 2 years ago
• vveitch / causal-network-embeddings
  Software and pre-processed data for "Using Embeddings to Correct for Unobserved Confounding in Networks"
  ☆56Updated 2 years ago
• bluer555 / KernelGCN
  Codes for NIPS 2019 Paper: Rethinking Kernel Methods for Node Representation Learning on Graphs
  ☆34Updated 5 years ago
• BorisMuzellec / EllipticalEmbeddings
  Python code for implementing embeddings in the Wasserstein space of elliptical distributions
  ☆11Updated 4 years ago