10 papers
PolySim: Deterministic Polynomial Surrogates for Cross-Modal Retrieval on CiM
Xinzhao Li, Charles Power, Pengyu Ren +10
Cross-modal retrieval on edge devices benefits from probabilistic embeddings that capture semantic uncertainty, but deploying them on compute-in-memory (CiM) hardware remains an op…
Probabilistic Memory for Trustworthy Edge Intelligence
Likai Pei, Jiahao Zheng, Xueji Zhao +9
Probabilistic computation plays an important role in trustworthy edge intelligence to quantify uncertainty, enhance robustness, reconstruct data, and protect privacy, but its adopt…
A 185 TOPS/W/mm2 Bayesian Inference Engine with 640 aJ Write-Free FeFET GRNG for Uncertainty-Aware Aerial Search and Rescue
Zephan M. Enciso, Xuezhong Niu, Xingtian Wang +9
Aerial search and rescue missions require fast and reliable victim detection under uncertain and rapidly changing environments. Deterministic deep learning models can produce overc…
A 65 nm Multi-Modal Bayesian Inference Engine with 16.3 fJ/Sample Calibration-Free GRNG for Risk-Aware At-Home Skin Lesion Screening
Steven Davis, Likai Pei, Jianbo Liu +5
We present a 65-nm risk-aware multimodal Bayesian inference engine for privacy-preserving, fully on-device skin lesion screening under uncontrolled at-home conditions. The proposed…
A 65-nm Privacy-Preserving Neuromorphic Encoder With 7.13-nJ Efficiency, 2.38-Mb/mm^2 Item-Memory Density, and Federated Learning Support
Boyang Cheng, Jianbo Liu, Steven Davis +5
The increasing demand for privacy-preserving personal data analytics in smart assistants, wearable health monitors, and context-aware systems calls for hardware that is both energy…
A 65 nm Trustworthy Hypoglycemia Forecasting Engine Achieving 11.3 nJ per Inference
Boyang Cheng, Jianbo Liu, Pengyu Ren +6
Diabetes affects millions of people and requires reliable continuous glucose monitoring for early hypoglycemia warning. However, medical AI systems must be not only accurate and en…