# Large-N dynamics of the spiked tensor model with random initial conditions

arXiv: https://arxiv.org/abs/2208.12586 · HTML: https://mlsanity.com/paper/2208.12586/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 4 of its 15 references that are in the map.
- First posted on arXiv 26 Aug 2022.

## Builds on (most cited first, 4 of 4)

- [A statistical model for tensor PCA](https://mlsanity.com/paper/1411.1076/) (2014)
- [The landscape of the spiked tensor model](https://mlsanity.com/paper/1711.05424/) (2017)
- [Marvels and Pitfalls of the Langevin Algorithm in Noisy High-dimensional Inference](https://mlsanity.com/paper/1812.09066/) (2018)
- [Complex energy landscapes in spiked-tensor and simple glassy models: ruggedness, arrangements of local minima and phase transitions](https://mlsanity.com/paper/1804.02686/) (2018)

## Abstract (arXiv)

In these notes, we develop a path integral approach for the partial differential equations with random initial conditions. Then, we apply it to the dynamics of the spiked tensor model and show that the large-N saddle point equations are dominated by the melonic type diagrams.