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- One Hidden Layer Neural Network Neural Networks Overview
- Fastwave: Accelerating Autoregressive Convolutional Neural Networks on FPGA
- Autoencoder-15-Mar-17.Pdf
- Efficient Contextual Representation Learning with Continuous Outputs
- Lecture 13 Convolutional Neural Network Architectures
- Machine Learning for Application-Layer Intrusion Detection
- Foundations of Artificial Intelligence
- Deep Learning at the Physical Layer: System Challenges and Applications to 5G and Beyond Francesco Restuccia, Member, IEEE, and Tommaso Melodia, Fellow, IEEE
- Compressing Deep Neural Networks Via Layer Fusion
- 14.1 Autoencoders
- Accelerating Training of Transformer-Based Language Models with Progressive Layer Dropping
- Autoencoder Based Residual Deep Networks for Robust Regression Prediction and Spatiotemporal Estimation
- Arxiv:2004.03829V2 [Cs.CL] 21 Sep 2020
- Backpropagation
- Multilayer Neural Networks
- Deep Learning for NLP
- Generative Pretraining from Pixels
- Deep Learning Architectures for Face Recognition in Video Surveillance
- "Deep Faking" Political Twitter Using Transfer Learning and GPT-2
- A State-Of-The-Art Survey on Deep Learning Theory and Architectures
- Flowavenet : a Generative Flow for Raw Audio
- Language Models Are Unsupervised Multitask Learners
- Performance Evaluation of Convolutional Neural Networks (Cnns) and VGG on Real Time Face Recognition System Showkat Ahmad Dar*, S Palanivel
- Linked Recurrent Neural Networks
- Machine Learning for PHY and MAC Layers
- Deep Learning - Alexnet Bernhard Kainz
- Short-Term Load Forecasting Using Encoder-Decoder Wavenet: Application to the French Grid
- Convolutional Neural Network for Face Recognition with Pose and Illumination Variation A
- A Multilayer Neural Network Merging Image Preprocessing and Pattern Recognition by Integrating Diffusion and Drift Memristors
- 7 the Backpropagation Algorithm
- Supervised Representation Learning with Double Encoding-Layer Autoencoder for Transfer Learning
- Autoencoders
- Unsupervised Learning: Deep Auto-Encoder Credits
- A Van Den Oord Et Al, “Wavenet: a Generative Model for Raw Audio”, Arxiv:1609.03499
- Memristor Neural Network Design Memristor Neural Network Design
- Pretrained Language Models for Dialogue Generation with Multiple Input Sources
- Artificial Neural Networks and Application to Thunderstorm Prediction
- Graph Wavenet for Deep Spatial-Temporal Graph Modeling
- Convolutional Neural Networks with Intra-Layer Recurrent Connections for Scene Labeling
- Lecture 4: Optimization and Backpropagation
- Artificial Neural Networks
- Explainable Artificial Intelligence: Understanding, Visualizing and Interpreting Deep Learning Models
- Wavenet: a Generative Model for Raw Audio
- A System of Different Layers of Abstraction for Artificial Intelligence
- Lecture 10 Recurrent Neural Networks
- Imagenet Classification with Deep Convolutional
- Layer Recurrent Neural Networks
- Accelerating On-Device Learning with Layer-Wise Processor Selection Method on Unified Memory
- Stochastic Wavenet: a Generative Latent Variable Model for Sequential Data
- Explainable AI: a Review of Machine Learning Interpretability Methods
- Wide Hidden Expansion Layer for Deep Convolutional Neural Networks
- An Introduction to Deep Learning for the Physical Layer Tim O’Shea, Senior Member, IEEE, and Jakob Hoydis, Member, IEEE
- Lecture 2: Deep Learning Fundamentals
- Optimization of a Pre-Trained Alexnet Model for Detecting and Localizing Image Forgeries
- Beyond Finite Layer Neural Networks: Bridging Deep Architectures and Numerical Differential Equations
- A Review of Recurrent Neural Networks: LSTM Cells and Network Architectures
- Sparse Autoencoder, CS294A Lecture Notes
- Parallel Wavenet: Fast High-Fidelity Speech Synthesis
- Memristor-Based Circuit Design for Multilayer Neural Networks Yang Zhang, Xiaoping Wang, Member, IEEE, and Eby G
- Implementing Wavenet Using Intel® Stratix® 10 NX FPGA for Real-Time Speech Synthesis
- Face Recognition System Based on Different Artificial Neural Networks Models and Training Algorithms
- Face Recognition System
- CSC 411 Lecture 10: Neural Networks I
- Deep Learning 13.3. Transformer Networks