Automatic Gradient Estimation for Calibrating Crowd Models with Discrete Decision Making

Author:

Andelfinger PhilippORCID,Kreikemeyer Justin N.ORCID

Publisher

Springer Nature Switzerland

Reference34 articles.

1. Andelfinger, P.: Towards differentiable agent-based simulation. ACM Trans. Model. Comput. Simul. 32(4), 1–26 (2023)

2. Arya, G., Schauer, M., Schäfer, F., Rackauckas, C.: Automatic differentiation of programs with discrete randomness. In: Koyejo, S., Mohamed, S., Agarwal, A., Belgrave, D., Cho, K., Oh, A. (eds.) Advances in Neural Information Processing Systems, vol. 35, pp. 10435–10447. Curran Associates, Inc. (2022)

3. Bengio, Y., Léonard, N., Courville, A.: Estimating or propagating gradients through stochastic neurons for conditional computation. arXiv preprint arXiv:1308.3432 (2013)

4. Bode, N.: Parameter calibration in crowd simulation models using approximate bayesian computation. arXiv preprint arXiv:2001.10330 (2020)

5. Chaudhuri, S., Solar-Lezama, A.: Smooth interpretation. ACM SIGPLAN Not. 45(6), 279–291 (2010)

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