IEEE

Efficient Precision-Adjustable Architecture for Softmax Function in Deep Learning

Abstract: The softmax function has been widely used in deep neural networks (DNNs), and studies on efficient hardware accelerators for DNN have also attracted tremendous attention. However, it is very ...
IEEE

Dual Balanced Class-Incremental Learning With im-Softmax and Angular Rectification

Abstract: Owing to the superior performances, exemplar-based methods with knowledge distillation (KD) are widely applied in class incremental learning (CIL). However, it suffers from two drawbacks: 1) ...
Scientific Research Publishing

Multimodal Digital Phenotyping for Bipolar Disorder: Robust Mood-State Classification and Early Relapse Risk Monitoring ()

Bipolar Disorder, Digital Phenotyping, Multimodal Learning, Face/Voice/Phone, Mood Classification, Relapse Prediction, T-SNE, Ablation Share and Cite: de Filippis, R. and Al Foysal, A. (2025) ...
GitHub

Simple Softmax-free Attention for Vision Transformer (SimA)

@misc{https://doi.org/10.48550/arxiv.2206.08898, doi = {10.48550/ARXIV.2206.08898}, url = {https://arxiv.org/abs/2206.08898}, author = {Koohpayegani, Soroush Abbasi ...
GitHub

lijin-THU/notes-python

中文 Python 笔记. Contribute to lijin-THU/notes-python development by creating an account on GitHub.