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Found 5 papers, 1 papers with code
RIS-Based On-the-Air Semantic Communications -- a Diffractional Deep Neural Network Approach
Semantic communication has gained significant attention recently due to its advantages in achieving higher transmission efficiency by focusing on semantic information instead of bit-level information.
Improving Realistic Worst-Case Performance of NVCiM DNN Accelerators through Training with Right-Censored Gaussian Noise
In this work, we propose to use the k-th percentile performance (KPP) to capture the realistic worst-case performance of DNN models executing on CiM accelerators.
On the Viability of using LLMs for SW/HW Co-Design: An Example in Designing CiM DNN Accelerators
In this study, we present a novel approach that leverages Large Language Models (LLMs) to address this issue.
Negative Feedback Training: A Novel Concept to Improve Robustness of NVCIM DNN Accelerators
However, the stochastic nature and intrinsic variations of NVM devices often result in performance degradation in DNN inference.
CryoFormer: Continuous Heterogeneous Cryo-EM Reconstruction using Transformer-based Neural Representations
Cryo-electron microscopy (cryo-EM) allows for the high-resolution reconstruction of 3D structures of proteins and other biomolecules.
