Update README.md

README.md

@@ -6812,102 +6812,288 @@ We encourage you to use the following BibTeX citation for MUSES itself:
 # TODO @Jimmy Add here Final Paper
 ```
 
-
 If you use MUSES, please also cite all the individual datasets you use, both to give the original authors their due credit and because venues will expect papers to describe the data they evaluate on.
 The following provides BibTeX for all of the MUSES tasks.
 
-# TODO MORITZ: Please Add original DS Papers like this
-
-für jedes DS zitieren:
-- data source paper, preproc source paper
-in ``` @citation{} ```
-
+#### earthquake
 ```
-@article{warstadt2018neural,
-  title={Neural Network Acceptability Judgments},
-  author={Warstadt, Alex and Singh, Amanpreet and Bowman, Samuel R.},
-  journal={arXiv preprint 1805.12471},
-  year={2018}
-}
-@inproceedings{socher2013recursive,
-  title={Recursive deep models for semantic compositionality over a sentiment treebank},
-  author={Socher, Richard and Perelygin, Alex and Wu, Jean and Chuang, Jason and Manning, Christopher D and Ng, Andrew and Potts, Christopher},
-  booktitle={Proceedings of EMNLP},
-  pages={1631--1642},
-  year={2013}
+@article{stockman2024earthquakenpp,
+  title={EarthquakeNPP: A Benchmark for Earthquake Forecasting with Neural Point Processes},
+  author={Stockman, Samuel and Lawson, Daniel and Werner, Maximilian},
+  journal={arXiv preprint arXiv:2410.08226},
+  year={2024}
 }
 ```
-#### earthquake
-
-
 
 #### memetrack
-
-
+```
+@inproceedings{leskovec2009meme,
+  title={Meme-tracking and the dynamics of the news cycle},
+  author={Leskovec, Jure and Backstrom, Lars and Kleinberg, Jon},
+  booktitle={Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining},
+  pages={497--506},
+  year={2009}
+}
+@article{mei2017neural,
+  title={The neural hawkes process: A neurally self-modulating multivariate point process},
+  author={Mei, Hongyuan and Eisner, Jason M},
+  journal={Advances in neural information processing systems},
+  volume={30},
+  year={2017}
+}
+```
 
 #### stackoverflow
-
-
+```
+@inproceedings{du2016recurrent,
+  title={Recurrent marked temporal point processes: Embedding event history to vector},
+  author={Du, Nan and Dai, Hanjun and Trivedi, Rakshit and Upadhyay, Utkarsh and Gomez-Rodriguez, Manuel and Song, Le},
+  booktitle={Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining},
+  pages={1555--1564},
+  year={2016}
+}
+```
 
 #### taxi_nyc_neighborhoods
-
-
+```
+@inproceedings{du2016recurrent,
+  title={Recurrent marked temporal point processes: Embedding event history to vector},
+  author={Du, Nan and Dai, Hanjun and Trivedi, Rakshit and Upadhyay, Utkarsh and Gomez-Rodriguez, Manuel and Song, Le},
+  booktitle={Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining},
+  pages={1555--1564},
+  year={2016}
+}
+```
 
 #### synthea
-
-
+```
+@article{walonoski2018synthea,
+  title={Synthea: An approach, method, and software mechanism for generating synthetic patients and the synthetic electronic health care record},
+  author={Walonoski, Jason and Kramer, Mark and Nichols, Joseph and Quina, Andre and Moesel, Chris and Hall, Dylan and Duffett, Carlton and Dube, Kudakwashe and Gallagher, Thomas and McLachlan, Scott},
+  journal={Journal of the American Medical Informatics Association},
+  volume={25},
+  number={3},
+  pages={230--238},
+  year={2018},
+  publisher={Oxford University Press}
+}
+@inproceedings{enguehard2020neural,
+  title={Neural temporal point processes for modelling electronic health records},
+  author={Enguehard, Joseph and Busbridge, Dan and Bozson, Adam and Woodcock, Claire and Hammerla, Nils},
+  booktitle={Machine Learning for Health},
+  pages={85--113},
+  year={2020},
+  organization={PMLR}
+}
+```
 
 #### spiketrains
-
-
+```
+@article{stetter2012model,
+  title={Model-free reconstruction of excitatory neuronal connectivity from calcium imaging signals},
+  author={Stetter, Olav and Battaglia, Demian and Soriano, Jordi and Geisel, Theo},
+  year={2012},
+  publisher={Public Library of Science San Francisco, USA}
+}
+@article{linderman2015scalable,
+  title={Scalable bayesian inference for excitatory point process networks},
+  author={Linderman, Scott W and Adams, Ryan P},
+  journal={arXiv preprint arXiv:1507.03228},
+  year={2015}
+}
+```
 
 #### crypto_transactions
-
-
+```
+@article{shamsi2022chartalist,
+  title={Chartalist: Labeled graph datasets for utxo and account-based blockchains},
+  author={Shamsi, Kiarash and Victor, Friedhelm and Kantarcioglu, Murat and Gel, Yulia and Akcora, Cuneyt G},
+  journal={Advances in Neural Information Processing Systems},
+  volume={35},
+  pages={34926--34939},
+  year={2022}
+}
+@inproceedings{du2016recurrent,
+  title={Recurrent marked temporal point processes: Embedding event history to vector},
+  author={Du, Nan and Dai, Hanjun and Trivedi, Rakshit and Upadhyay, Utkarsh and Gomez-Rodriguez, Manuel and Song, Le},
+  booktitle={Proceedings of the 22nd ACM SIGKDD international conference on knowledge discovery and data mining},
+  pages={1555--1564},
+  year={2016}
+}
+```
 
 #### human_activity
-
-
+```
+@article{cook2012casas,
+  title={CASAS: A smart home in a box},
+  author={Cook, Diane J and Crandall, Aaron S and Thomas, Brian L and Krishnan, Narayanan C},
+  journal={Computer},
+  volume={46},
+  number={7},
+  pages={62--69},
+  year={2012},
+  publisher={IEEE}
+}
+@article{fortino2021predicting,
+  title={Predicting activities of daily living via temporal point processes: Approaches and experimental results},
+  author={Fortino, Giancarlo and Guzzo, Antonella and Ianni, Michele and Leotta, Francesco and Mecella, Massimo},
+  journal={Computers \& Electrical Engineering},
+  volume={96},
+  pages={107567},
+  year={2021},
+  publisher={Elsevier}
+}
+```
 
 #### 911
-
-
+```
+@inproceedings{zuo2020transformer,
+  title={Transformer hawkes process},
+  author={Zuo, Simiao and Jiang, Haoming and Li, Zichong and Zhao, Tuo and Zha, Hongyuan},
+  booktitle={International conference on machine learning},
+  pages={11692--11702},
+  year={2020},
+  organization={PMLR}
+}
+```
 
 #### mooc
-
-
+```
+@inproceedings{kumar2019predicting,
+  title={Predicting dynamic embedding trajectory in temporal interaction networks},
+  author={Kumar, Srijan and Zhang, Xikun and Leskovec, Jure},
+  booktitle={Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery \& data mining},
+  pages={1269--1278},
+  year={2019}
+}
+@article{shchur2019intensity,
+  title={Intensity-free learning of temporal point processes},
+  author={Shchur, Oleksandr and Bilo{\v{s}}, Marin and G{\"u}nnemann, Stephan},
+  journal={arXiv preprint arXiv:1909.12127},
+  year={2019}
+}
+```
 
 #### amazon_easytpp
-
-
+```
+@inproceedings{ni2019justifying,
+  title={Justifying recommendations using distantly-labeled reviews and fine-grained aspects},
+  author={Ni, Jianmo and Li, Jiacheng and McAuley, Julian},
+  booktitle={Proceedings of the 2019 conference on empirical methods in natural language processing and the 9th international joint conference on natural language processing (EMNLP-IJCNLP)},
+  pages={188--197},
+  year={2019}
+}
+@article{xue2023easytpp,
+  title={Easytpp: Towards open benchmarking temporal point processes},
+  author={Xue, Siqiao and Shi, Xiaoming and Chu, Zhixuan and Wang, Yan and Hao, Hongyan and Zhou, Fan and Jiang, Caigao and Pan, Chen and Zhang, James Y and Wen, Qingsong and others},
+  journal={arXiv preprint arXiv:2307.08097},
+  year={2023}
+}
+```
 
 #### wikipedia
-
-
+```
+@inproceedings{kumar2019predicting,
+  title={Predicting dynamic embedding trajectory in temporal interaction networks},
+  author={Kumar, Srijan and Zhang, Xikun and Leskovec, Jure},
+  booktitle={Proceedings of the 25th ACM SIGKDD international conference on knowledge discovery \& data mining},
+  pages={1269--1278},
+  year={2019}
+}
+@article{bosser2023predictive,
+  title={On the predictive accuracy of neural temporal point process models for continuous-time event data},
+  author={Bosser, Tanguy and Taieb, Souhaib Ben},
+  journal={arXiv preprint arXiv:2306.17066},
+  year={2023}
+}
+```
 
 #### retweet_easytpp
-
-
+```
+@inproceedings{zhao2015seismic,
+  title={Seismic: A self-exciting point process model for predicting tweet popularity},
+  author={Zhao, Qingyuan and Erdogdu, Murat A and He, Hera Y and Rajaraman, Anand and Leskovec, Jure},
+  booktitle={Proceedings of the 21th ACM SIGKDD international conference on knowledge discovery and data mining},
+  pages={1513--1522},
+  year={2015}
+}
+@article{xue2023easytpp,
+  title={Easytpp: Towards open benchmarking temporal point processes},
+  author={Xue, Siqiao and Shi, Xiaoming and Chu, Zhixuan and Wang, Yan and Hao, Hongyan and Zhou, Fan and Jiang, Caigao and Pan, Chen and Zhang, James Y and Wen, Qingsong and others},
+  journal={arXiv preprint arXiv:2307.08097},
+  year={2023}
+}
+```
 
 #### taobao_easytpp
-
-
+```
+@article{xue2022hypro,
+  title={Hypro: A hybridly normalized probabilistic model for long-horizon prediction of event sequences},
+  author={Xue, Siqiao and Shi, Xiaoming and Zhang, James and Mei, Hongyuan},
+  journal={Advances in Neural Information Processing Systems},
+  volume={35},
+  pages={34641--34650},
+  year={2022}
+}
+@article{xue2023easytpp,
+  title={Easytpp: Towards open benchmarking temporal point processes},
+  author={Xue, Siqiao and Shi, Xiaoming and Chu, Zhixuan and Wang, Yan and Hao, Hongyan and Zhou, Fan and Jiang, Caigao and Pan, Chen and Zhang, James Y and Wen, Qingsong and others},
+  journal={arXiv preprint arXiv:2307.08097},
+  year={2023}
+}
+```
 
 #### taxi_easytpp
-
-
+```
+@article{xue2023easytpp,
+  title={Easytpp: Towards open benchmarking temporal point processes},
+  author={Xue, Siqiao and Shi, Xiaoming and Chu, Zhixuan and Wang, Yan and Hao, Hongyan and Zhou, Fan and Jiang, Caigao and Pan, Chen and Zhang, James Y and Wen, Qingsong and others},
+  journal={arXiv preprint arXiv:2307.08097},
+  year={2023}
+}
+```
 
 #### volcano_easytpp
-
-
+```
+@article{bebbington2014long,
+  title={Long-term forecasting of volcanic explosivity},
+  author={Bebbington, MS},
+  journal={Geophysical Journal International},
+  volume={197},
+  number={3},
+  pages={1500--1515},
+  year={2014},
+  publisher={Oxford University Press}
+}
+@misc{easytpp-github-volcano,
+  title = {EasyTemporalPointProcess GitHub Volcano Preprocessing},
+  author = {Xue, Siqiao and Shi, Xiaoming and Chu, Zhixuan and Wang, Yan and Hao, Hongyan and Zhou, Fan and Jiang, Caigao and Pan, Chen and Zhang, James Y and Wen, Qingsong and others},
+  url = {https://github.com/ant-research/EasyTemporalPointProcess/blob/main/examples/script_data_processing/volcano.py}
+}
+```
 
 #### hawkes_dependent
-
-
+```
+@inproceedings{enguehard2020neural,
+  title={Neural temporal point processes for modelling electronic health records},
+  author={Enguehard, Joseph and Busbridge, Dan and Bozson, Adam and Woodcock, Claire and Hammerla, Nils},
+  booktitle={Machine Learning for Health},
+  pages={85--113},
+  year={2020},
+  organization={PMLR}
+}
+```
 
 #### hawkes_1
-
-
+```
+@article{omi2019fully,
+  title={Fully neural network based model for general temporal point processes},
+  author={Omi, Takahiro and Aihara, Kazuyuki and others},
+  journal={Advances in neural information processing systems},
+  volume={32},
+  year={2019}
+}
+```
 
 ### Contributions