1 code implementation • 8 May 2024 • John-Joseph Brady, Yuhui Luo, Wenwu Wang, Victor Elvira, Yunpeng Li
Differentiable particle filters are an emerging class of models that combine sequential Monte Carlo techniques with the flexibility of neural networks to perform state space inference.
no code implementations • 2 May 2024 • Jiaxi Li, John-Joseph Brady, Xiongjie Chen, Yunpeng Li
Differentiable particle filters combine the flexibility of neural networks with the probabilistic nature of sequential Monte Carlo methods.
