Compressing VAE-Based Out-of-Distribution Detectors for Embedded Deployment
The research combines quantization, pruning, and knowledge distillation to create lean Variational Autoencoder (VAE) based Out-of-Distribution (OOD) detectors for embedded systems. This multi-stage compression methodology significantly reduces memory and execution time on CPUs and GPUs while maintaining acceptable OOD detection accuracy.