You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardExpand all lines: README.md
+6-2
Original file line number
Diff line number
Diff line change
@@ -28,19 +28,23 @@ Track of developments in Temporal Point Processes (TPPs)
28
28
*[EasyTPP: Towards Open Benchmarking Temporal Point Processes](https://arxiv.org/abs/2307.08097)[ICLR-2024][](https://github.com/ant-research/EasyTemporalPointProcess)
29
29
*[Learning Multivariate Temporal Point Processes via the Time-Change Theorem](https://proceedings.mlr.press/v238/augusto-zagatti24a/augusto-zagatti24a.pdf)[AISTATS-2024][](https://github.com/NUS-IDS/multi-ttpp)
30
30
*[A Variational Autoencoder for Neural Temporal Point Processes with Dynamic Latent Graphs](https://arxiv.org/abs/2312.16083)[AAAI-2024][](https://github.com/sikunyang/VAETPP)
31
+
*[Interacting Diffusion Processes for Event Sequence Forecasting](https://arxiv.org/abs/2310.17800)[ICML-2024][](https://github.com/networkslab/cdiff)
32
+
*[Neural Jump-Diffusion Temporal Point Processes](https://openreview.net/pdf?id=d1P6GtRzuV)[ICML-2024][](https://github.com/Zh-Shuai/NJDTPP)
31
33
32
34
## 2023
33
35
*[Bellman Meets Hawkes: Model-Based Reinforcement Learning via Temporal Point Processes](https://arxiv.org/abs/2201.12569)[AAAI-2023][](https://github.com/WilliamBUG/Event_driven_rl)
34
36
*[Add and thin: Diffusion for temporal point processes](https://arxiv.org/abs/2311.01139)[NeurIPS-2023][](https://github.com/davecasp/add-thin)
35
37
*[Sparse Transformer Hawkes Process for Long Event Sequences](https://link.springer.com/chapter/10.1007/978-3-031-43424-2_11)[ECML-PKDD-2023]
38
+
*[ContiFormer: Continuous-Time Transformer for Irregular Time Series Modeling](https://arxiv.org/abs/2402.10635)[NeurIPS-2023][](https://github.com/microsoft/SeqML)
39
+
*[Integration-free Training for Spatio-temporal Multimodal Covariate Deep Kernel Point Processes](https://arxiv.org/abs/2310.05485)[NeurIPS-2023]
40
+
*[Prompt-augmented Temporal Point Process for Streaming Event Sequence](https://arxiv.org/abs/2310.04993)[NeurIPS-2023][](https://github.com/yanyanSann/PromptTPP)
36
41
*[Language Models Can Improve Event Prediction by Few-Shot Abductive Reasoning](https://arxiv.org/abs/2305.16646)[NeurIPS-2023][](https://github.com/iLampard/lamp)
*[C-NTPP: Learning Cluster-Aware Neural Temporal Point Process](https://ojs.aaai.org/index.php/AAAI/article/view/25897/25669)[AAAI-2023]
39
44
*[Meta Temporal Point Processes](https://arxiv.org/abs/2301.12023)[ICLR-2023]
40
-
*[Integration-free Training for Spatio-temporal Multimodal Covariate Deep Kernel Point Processes](https://arxiv.org/abs/2310.05485)[NeurIPS-2023]
41
-
*[Prompt-augmented Temporal Point Process for Streaming Event Sequence](https://arxiv.org/abs/2310.04993)[NeurIPS-2023][](https://github.com/yanyanSann/PromptTPP)
42
45
*[Probabilistic Querying of Continuous-Time Event Sequences](https://arxiv.org/abs/2211.08499)[AISTATS-2023][](https://github.com/ajboyd2/point_process_queries)
43
46
*[Structural Hawkes Processes for Learning Causal Structure from Discrete-Time Event Sequences](https://arxiv.org/abs/2305.05986)[IJCAI-2023][](https://github.com/dmirlab-group/shp)
47
+
*[Spatio-temporal Diffusion Point Processes](https://arxiv.org/abs/2305.12403)[KDD-2023][](https://github.com/tsinghua-fib-lab/Spatio-temporal-Diffusion-Point-Processes)
44
48
45
49
## 2022
46
50
*[Exploring Generative Neural Temporal Point Process](https://arxiv.org/abs/2208.01874)[TMLR-2022][](https://github.com/bird-tao/gntpp)
0 commit comments