Meet DIsoN, our 🧹💨 privacy-preserving OOD detector that compares test samples to training data without ever sharing the training data.
We make Out-of-Distribution detection decentralized!
📄Paper: arxiv.org/pdf/2506.09024
🧵👇
Meet DIsoN, our 🧹💨 privacy-preserving OOD detector that compares test samples to training data without ever sharing the training data.
We make Out-of-Distribution detection decentralized!
📄Paper: arxiv.org/pdf/2506.09024
🧵👇
Meet DIsoN, our 🧹💨 privacy-preserving OOD detector that compares test samples to training data without ever sharing the training data.
We make Out-of-Distribution detection decentralized!
📄Paper: arxiv.org/pdf/2506.09024
🧵👇
🔗 arXiv: arxiv.org/pdf/2406.11636
💻 GitHub: github.com/FelixWag/Fed...
🧵1/N
🔗 arXiv: arxiv.org/pdf/2406.11636
💻 GitHub: github.com/FelixWag/Fed...
🧵1/N