https://github.com/lucidrains/kalmanformer
Implementation of Kalmanformer, modeling the Kalman gain with a transformer
https://github.com/lucidrains/kalmanformer
artificial-intelligence deep-learning kalman-filter state-estimation transformers
Last synced: 22 days ago
JSON representation
Implementation of Kalmanformer, modeling the Kalman gain with a transformer
- Host: GitHub
- URL: https://github.com/lucidrains/kalmanformer
- Owner: lucidrains
- License: mit
- Created: 2026-05-30T02:34:41.000Z (29 days ago)
- Default Branch: main
- Last Pushed: 2026-05-30T03:52:54.000Z (29 days ago)
- Last Synced: 2026-05-30T04:17:27.218Z (29 days ago)
- Topics: artificial-intelligence, deep-learning, kalman-filter, state-estimation, transformers
- Language: Python
- Homepage:
- Size: 217 KB
- Stars: 4
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
## KalmanFormer
Implementation of KalmanFormer.
The paper proposes learning the Kalman Gain directly from data using Transformers, bypassing the limitations of traditional Kalman Filters on non-linear systems.
## Install
```bash
$ pip install kalmanformer
```
## Usage
```python
import torch
from kalmanformer import KalmanFormer
# kalmanformer
kalmanformer = KalmanFormer(
state_dim = 3,
obs_dim = 3,
dim = 64,
depth = 2,
heads = 2,
dim_head = 32,
mlp_dim = 64
)
# mock observations
observations = torch.randn(2, 10, 3)
# state transition matrix f and observation matrix h
F = torch.randn(3, 3)
H = torch.randn(3, 3)
# initial state
x_0 = torch.zeros(2, 3)
# tracking over sequence
post_states = kalmanformer(
observations,
F,
H,
x_0 = x_0
)
assert post_states.shape == (2, 10, 3)
```
## Citations
```bibtex
@article{Shen2025KalmanFormer,
title = {KalmanFormer: using transformer to model the Kalman Gain in Kalman Filters},
author = {Siyuan Shen and Jichen Chen and Guanfeng Yu and Zhengjun Zhai and Pujie Han},
journal = {Frontiers in Neurorobotics},
year = {2025},
volume = {18},
doi = {10.3389/fnbot.2024.1460255}
}
```