Search Results for author:
Found 5 papers, 3 papers with code
Penetrative AI: Making LLMs Comprehend the Physical World
Recent developments in Large Language Models (LLMs) have demonstrated their remarkable capabilities across a range of tasks.
PriMask: Cascadable and Collusion-Resilient Data Masking for Mobile Cloud Inference
This paper presents the design of a system called PriMask, in which the mobile device uses a secret small-scale neural network called MaskNet to mask the data before transmission.
Enhancing Deep Learning Performance of Massive MIMO CSI Feedback
In this paper, we propose a jigsaw puzzles aided training strategy (JPTS) to enhance the deep learning-based Massive MIMO CSI feedback approaches by maximizing mutual information between the original CSI and the compressed CSI.
CLNet: Complex Input Lightweight Neural Network designed for Massive MIMO CSI Feedback
Numerous deep learning for massive MIMO CSI feedback approaches have demonstrated their efficiency and potential.
On-the-fly Closed-loop Autonomous Materials Discovery via Bayesian Active Learning
Active learning - the field of machine learning (ML) dedicated to optimal experiment design, has played a part in science as far back as the 18th century when Laplace used it to guide his discovery of celestial mechanics [1].
