The demonstrated AONN scheme can be used to construct various ANN architectures with intrinsic optical parallel computation. 中文翻译: 具有非线性激活函数的全光神经网络 人工神经网络(ANN)已广泛用于工业应用,并在基础研究中发挥了重要作用。尽管大多数ANN硬件系统都是基于电子的,但由于其固有的并行性和低能耗,...
oneDNN has experimental support for the following architectures: Arm* 64-bit Architecture (AArch64), NVIDIA* GPU, OpenPOWER* Power ISA (PPC64), IBMz* (s390x), and RISC-V.oneDNN is intended for deep learning applications and framework developers interested in improving application performance on...
⭐ subword-nmt - Unsupervised Word Segmentation for Neural Machine Translation and Text Generation [GitHub, 2185 stars] ⭐ python-bpe - Byte Pair Encoding for Python [GitHub, 223 stars] Transformer-based Architectures General 📙 The Transformer Family by Lilian Weng [Blog, 2020] 📙 Playing...
Our once-for-all network provides one model but supports manysub-networksof different sizes, covering four important dimensions of the convolutional neural networks (CNNs) architectures, i.e.,depth, width, kernel size, and resolution. 做法还是Follow common practice:用Block搭成一个自下而上的网络,...
parallel architectures/ optical neuron deviceoptical parallel operationsall-optical neural networksoptical neural network systemmassively parallel processing architectureWe propose a method for implementing an optical neural network system which utilizes a massively parallel processing architecture and aims to ...
来自麻省理工学院的韩松曾在 ICLR 多次发表论文,他的论文Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding获得了 2016 年 ICLR 的最佳论文奖。 而在2020 年,他的团队又带来了一项名为Once-for-All: Train One Network and Specialize it for Efficient Deplo...
particularly when combined with in-domain fine-tuning. Work with larger decoder-based architectures has also demonstrated a benefit with fine-tuning on medical data or prompt tuning with chain of thought, instructions and related techniques24,25, which further emphasizes the necessity of accounting for...
A Wu,Z Zeng,J Chen - 《Neural Computing & Applications》 被引量: 17发表: 2014年 A Winner-Take-All Method for Training Sparse Convolutional Autoencoders We explore combining the benefits of convolutional architectures and autoencoders for learning deep representations in an unsupervised manner. A...
Spiking neural network (SNN) has emerged as one of the popular architectures in complex pattern recognition and classification tasks. However, hardware imp... B Pan,K Wang,X Chen,... - IEEE International Symposium on Circuits & Systems 被引量: 0发表: 2019年 Magnetic skyrmion-based synaptic ...
来自麻省理工学院的韩松曾在 ICLR 多次发表论文,他的论文Deep Compression: Compressing Deep Neural Networks with Pruning, Trained Quantization and Huffman Coding获得了 2016 年 ICLR 的最佳论文奖。 而在2020 年,他的团队又带来了一项名为Once-for-All: Train One Network and Specialize it for Efficient Deplo...