Course to success: Coursera's CEO on the value of lifelong learning

Jeff Maggioncalda, CEO of online education provider Coursera, knows what it is like to put his professional life on pause.
Frontiers

Convolutional neural networks decode finger movements in motor sequence learning from MEG data

1 Institute of Cognitive Neuroscience, National Research University Higher School of Economics, Moscow, Russia 2 Department of Learning, Data Analytics and Technology, Section Cognition, Data and ...
eLife

Comprehensive Neural Representations of Naturalistic Stimuli through Multimodal Deep Learning

This study presents a valuable application of a video-text alignment deep neural network model to improve neural encoding of naturalistic stimuli in fMRI. The authors found that models based on ...
Phys.org

Using geometry and physics to explain feature learning in deep neural networks

Deep neural networks (DNNs), the machine learning algorithms underpinning the functioning of large language models (LLMs) and other artificial intelligence (AI) models, learn to make accurate ...
IEEE

Energy-efficient Distributed Heterogeneous Hybrid Flow-shop Scheduling Using Graph Neural Network and Deep Reinforcement Learning

Abstract: With growing environmental awareness and increasing energy demands, sustainable manufacturing has become a focal point in the industry. Meanwhile, globalization has propelled distributed ...
IEEE

Efficient Multiscale Hybrid Cross-learning Deep Neural Networks with Spatiotemporal Fusion for Vehicle Behavior Prediction

Abstract: Recently, deep neural network-based methods have been proposed for vehicle behavior prediction (VBP). However, existing methods lack an enhanced discriminative mechanism and robust learning ...
Phys.org

Self-learning neural network cracks iconic black holes

A team of astronomers led by Michael Janssen (Radboud University, The Netherlands) has trained a neural network with millions of synthetic black hole data sets. Based on the network and data from the ...
Scientific Research Publishing

Hybrid PINN-LSTM Model for River Temperature Prediction: A Physics-Informed Deep Learning Approach ()

This study proposes a hybrid modeling approach that integrates a Physics Informed Neural Network (PINN) and a long short-term memory (LSTM) network to predict river water temperature in a defined ...
C&EN

DeepEpiIL13: Deep Learning for Rapid and Accurate Prediction of IL-13-Inducing Epitopes Using Pretrained Language Models and Multiwindow Convolutional Neural Networks

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Accurate prediction of interleukin-13 (IL-13)-inducing epitopes is crucial for ...
GitHub

bsklzsc/1Flexible-Job-Shop-Scheduling-Via-Graph-Neural-Network-and-Deep-Reinforcement-Learning

Implementation of the IEEE TII paper Flexible Job Shop Scheduling via Graph Neural Network and Deep Reinforcement Learning. IEEE Transactions on Industrial Informatics, 2022. @ARTICLE{9826438, author= ...