Attention mechanism-based (Attn) temporal convolutional networks (TCN) connected with recurrent neural network (RNN) models for landslide risk prediction are proposed, including TCN-Attn-RNN and ...

This paper proposes an Encoder-Decoder neural network architecture with Attention Mechanism for solving the DRC-FJSSP using Deep Q-Learning. In the DRC-FJSSP the number of operations to schedule is ...

An NYU team uses machine learning to analyze neural activity data and uncover how speech is produced. In a recent paper ...

Recent brain-computer-interface (BCI) devices have made it possible to translate neural activity directly into text and even ...

"We present dissociative prioritized analysis of dynamics (DPAD), a nonlinear dynamical modeling approach that enables these capabilities with a multisection neural network architecture and training ...

By analyzing neural signals, a brain-computer interface can now almost instantaneously synthesize the speech of a man who lost use of his voice due to a neurodegenerative disease, a new study finds.

Structural Surrogate Model and Dynamic Response Prediction with Consideration of Temporal and Spatial Evolution: An Encoder–Decoder ConvLSTM Network ...