Killian Levacher
17Patents
2h-index
25Co-inventors
46Inventor score
Filing activity: Jan 2, 2018 → Mar 22, 2022
Most-cited inventions
| Patent | Title | Area | Cited by | Status |
|---|---|---|---|---|
| US10832009B2 | Extraction and summarization of decision elements from communications | Electricity | 4 | Active |
| US12182263B2 | Defending deep generative models against adversarial attacks | Physics | 2 | Active |
| US11176257B2 | Reducing risk of smart contracts in a blockchain | Electricity | 2 | Active |
| US11824894B2 | Defense of targeted database attacks through dynamic honeypot database response generation | Physics | 2 | Active |
| US11556938B2 | Managing regulatory compliance for an entity | Physics | 1 | Active |
| US11361055B1 | Protection of a content repository using dynamic watermarking | Physics | 1 | Active |
| US11315120B2 | Implementing a marketplace for risk assessed smart contracts issuers and execution providers in a blockchain | Physics | 1 | Active |
| US11023681B2 | Co-reference resolution and entity linking | Physics | 1 | Active |
| US11392487B2 | Synthetic deidentified test data | Physics | 1 | Active |
| US11562139B2 | Text data protection against automated analysis | Physics | 0 | Active |
| US12250150B2 | AI-based compensation of resource constrained communication | Physics | 0 | Active |
| US11222177B2 | Intelligent augmentation of word representation via character shape embeddings in a neural network | Physics | 0 | Active |
| US11842256B2 | Ensemble training in a distributed marketplace | Electricity | 0 | Active |
| US12242613B2 | Automated evaluation of machine learning models | Physics | 0 | Active |
| US12380217B2 | Federated generative models for website assessment | Physics | 0 | Active |
| US11562087B2 | Sensitive data policy recommendation based on compliance obligations of a data source | Physics | 0 | Active |
| US12321483B2 | Augmented privacy datasets using semantic based data linking | Physics | 0 | Active |
Source: USPTO / EPO open patent data. Inventor disambiguation is heuristic; counts are objective bibliographic measures.