Neural Jump Stochastic Differential Equations
Authors: Junteng Jia, Austin R. Benson
NeurIPS 2019 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Experimental | We demonstrate the predictive capabilities of our model on a range of synthetic and real-world marked point process datasets, including classical point processes (such as Hawkes processes), awards on Stack Overflow, medical records, and earthquake monitoring. |
| Researcher Affiliation | Academia | Junteng Jia Cornell University jj585@cornell.edu Austin R. Benson Cornell University arb@cs.cornell.edu |
| Pseudocode | Yes | The complete algorithm for simulating the hybrid system with stochastic events is described in Appendix A.1. |
| Open Source Code | Yes | The complete implementation of our algorithms and experiments are available at https://github.com/000Justin000/torchdiffeq/tree/jj585. |
| Open Datasets | Yes | We use our model to predict the time and locations of earthquakes above level 4.0 in 2007 2018 using historical data from 1970 2006. Data from https://www.kaggle.com/danielpe/earthquakes |
| Dataset Splits | Yes | For each generative process, we create a dataset by simulating 500 event sequences within the time interval [0, 100] and use 60% for training, 20% for validation and 20% for testing. |
| Hardware Specification | Yes | We train all of our models on a workstation with a 8 core i7-7700 CPU @ 3.60GHz processor and 32 GB memory. |
| Software Dependencies | No | The paper mentions using the "Adam optimizer" and refers to its implementation being available via a GitHub link that includes "torchdiffeq", but it does not provide specific version numbers for these or other software dependencies. |
| Experiment Setup | Yes | We use the Adam optimizer with β1 = 0.9, β2 = 0.999; the architectures, hyperparameters, and learning rates for different experiments are reported below. ... the learning rate for the Adam optimizer is set to be 10 3 with weighted decay rate 10 5. |