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GitHub10mon
idiap/sparse: SPARSE: Spiking Architectures towards Realistic Speech Encoding - GitHub
SPARSE: Spiking Architectures towards Realistic Speech Encoding - idiap/sparse. Skip to content. Navigation Menu Toggle navigation. Sign in ... import torch import torch.nn as nn from ...
IEEE13y
Learning sparse representation via a nonlinear shrinkage encoder and a linear sparse decoder
Abstract: Learning sparse representations for deep networks has drawn considerable research interest in recent years. In this paper, we present a novel framework to learn sparse representations via a ...
IEEE6y
Manifold Sparse Auto-Encoder for Machine Fault Diagnosis
Although the use of deep learning algorithms to find effective features for fault diagnosis has somewhat enhanced of fault classification accuracy, the lack of guidelines and the parameters such as ...
GitHub7mon
sanowl/Mixture-of-Transformers-A-Sparse-and-Scalable-Architecture-for-Multi-Modal-Foundation-Model-meta - GitHub
The MoT model architecture includes several critical components: Modality-Specific Transformer Layers: These separate transformer encoder layers process each modality independently, allowing the model ...
Semiconductor Engineering4mon
HW-Aligned Sparse Attention Architecture For Efficient Long-Context Modeling (DeepSeek et al.) - Semiconductor Engineering
A new technical paper titled “Native Sparse Attention: Hardware-Aligned and Natively Trainable Sparse Attention” was published by DeepSeek, Peking University and University of Washington. Abstract ...
Frontiers2y
Efficient feature extraction from highly sparse binary genotype data for cancer prognosis prediction using an auto-encoder - Frontiers
In addition, compared to highly sparse binary variables, low-dimensional continuous variables are better utilized. Therefore, we thought of using the auto-encoder to integrate such highly sparse ...