Jinfeng Yi
17Patents
3h-index
18Co-inventors
49Inventor score
Filing activity: Feb 8, 2013 → Dec 29, 2020
Most-cited inventions
| Patent | Title | Area | Cited by | Status |
|---|---|---|---|---|
| US9208219B2 | Similar document detection and electronic discovery | Physics | 8 | Active |
| US9418144B2 | Similar document detection and electronic discovery | Physics | 4 | Active |
| US10395180B2 | Privacy and modeling preserved data sharing | Physics | 3 | Active |
| US11093818B2 | Customer profile learning based on semi-supervised recurrent neural network using partially labeled sequence data | Physics | 3 | Active |
| US11301773B2 | Method and system for time series representation learning via dynamic time warping | Physics | 2 | Active |
| US9743243B1 | Location context inference based on user mobile data with uncertainty | Electricity | 2 | Active |
| US11281994B2 | Method and system for time series representation learning via dynamic time warping | Physics | 2 | Active |
| US10395182B2 | Privacy and modeling preserved data sharing | Physics | 1 | Active |
| US9639598B2 | Large-scale data clustering with dynamic social context | Physics | 0 | Active |
| US10003923B2 | Location context inference based on user mobile data with uncertainty | Electricity | 0 | Active |
| US10896371B2 | Multi-dimensional time series event prediction via convolutional neural network(s) | Physics | 0 | Active |
| US11366990B2 | Time-series representation learning via random time warping | Physics | 0 | Active |
| US10891545B2 | Multi-dimensional time series event prediction via convolutional neural network(s) | Physics | 0 | Active |
| US10678800B2 | Recommendation prediction based on preference elicitation | Physics | 0 | Active |
| US12165058B2 | Multi-dimensional time series event prediction via convolutional neural network(s) | Physics | 0 | Active |
| US10970603B2 | Object recognition and description using multimodal recurrent neural network | Physics | 0 | Active |
| US10692099B2 | Feature learning on customer journey using categorical sequence data | Physics | 0 | Active |
Source: USPTO / EPO open patent data. Inventor disambiguation is heuristic; counts are objective bibliographic measures.