2 citations · 2 across the 3 of their papers we have counts for
3 papers
cs.LG2024
Revisiting semi-supervised training objectives for differentiable particle filters
Jiaxi Li, John-Joseph Brady, Xiongjie Chen +1
Differentiable particle filters combine the flexibility of neural networks with the probabilistic nature of sequential Monte Carlo methods. However, traditional approaches rely on…
cs.AI2022
Conditional Measurement Density Estimation in Sequential Monte Carlo via Normalizing Flow
Xiongjie Chen, Yunpeng Li
Tuning of measurement models is challenging in real-world applications of sequential Monte Carlo methods. Recent advances in differentiable particle filters have led to various eff…
cs.LG2020★ 2 cited
End-To-End Semi-supervised Learning for Differentiable Particle Filters
Hao Wen, Xiongjie Chen, Georgios Papagiannis +2
Recent advances in incorporating neural networks into particle filters provide the desired flexibility to apply particle filters in large-scale real-world applications. The dynamic…