Notice: The reproducibility variables underlying each score are classified using an automated LLM-based pipeline, validated against a manually labeled dataset. LLM-based classification introduces uncertainty and potential bias; scores should be interpreted as estimates. Full accuracy metrics and methodology are described in [1].
Learning Hawkes Processes from Short Doubly-Censored Event Sequences
Authors: Hongteng Xu, Dixin Luo, Hongyuan Zha
ICML 2017 | Venue PDF | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | Experiments on both synthetic and real-world data demonstrate that the proposed data synthesis method improves learning results indeed for both timeinvariant and time-varying Hawkes processes. |
| Researcher Affiliation | Academia | 1Georgia Institute of Technology, Atlanta, Georgia, USA 2University of Toronto, Toronto, Ontario, Canada. |
| Pseudocode | Yes | Algorithm 1 Learning Algorithm of Hawkes Processes |
| Open Source Code | No | The paper does not provide any statements or links indicating the availability of open-source code for the methodology described. |
| Open Datasets | Yes | MIMIC III Data. The MIMIC III data contain admission records of over 40, 000 patients in the Beth Israel Deaconess Medical Center between 2001 and 2012. ... Johnson, Alistair EW, Pollard, Tom J, Shen, Lu, Lehman, Li-wei H, Feng, Mengling, Ghassemi, Mohammad, Moody, Benjamin, Szolovits, Peter, Celi, Leo Anthony, and Mark, Roger G. Mimic-iii, a freely accessible critical care database. Scientific data, 3, 2016. |
| Dataset Splits | No | The paper mentions 'testing set' and 'training set' for all datasets but does not explicitly describe a separate 'validation' set or its split details. |
| Hardware Specification | No | The paper does not explicitly describe the hardware specifications (e.g., CPU, GPU models, memory) used to run the experiments. |
| Software Dependencies | No | The paper does not provide specific software names with version numbers required to reproduce the experiments. |
| Experiment Setup | Yes | In the following experiments, we use Gaussian basis functions: κm(t) = exp((t tm)2/σκ) with center tm and bandwidth σκ. ... Additionally, we set V = 10 4, γ = 1, and σs = 1 in our algorithm. |