Artificial intelligence for industry 4.0: Systematic review of applications, challenges, and opportunities
Many industry sectors have been pursuing the adoption of Industry 4.0 (I4. 0) ideas and
technologies, which promise to realize lean and just-in-time production through digitization …
technologies, which promise to realize lean and just-in-time production through digitization …
Root mean square error (RMSE) or mean absolute error (MAE): When to use them or not
TO Hodson - Geoscientific Model Development Discussions, 2022 - gmd.copernicus.org
The mean absolute error (MAE) and root mean squared error (RMSE) are widely used
metrics for evaluating models. Yet, there remains enduring confusion over their use, such …
metrics for evaluating models. Yet, there remains enduring confusion over their use, such …
Illuminating protein space with a programmable generative model
Three billion years of evolution has produced a tremendous diversity of protein molecules,
but the full potential of proteins is likely to be much greater. Accessing this potential has …
but the full potential of proteins is likely to be much greater. Accessing this potential has …
Edge learning for B5G networks with distributed signal processing: Semantic communication, edge computing, and wireless sensing
To process and transfer large amounts of data in emerging wireless services, it has become
increasingly appealing to exploit distributed data communication and learning. Specifically …
increasingly appealing to exploit distributed data communication and learning. Specifically …
Quantum advantage in learning from experiments
Quantum technology promises to revolutionize how we learn about the physical world. An
experiment that processes quantum data with a quantum computer could have substantial …
experiment that processes quantum data with a quantum computer could have substantial …
A comprehensive survey on poisoning attacks and countermeasures in machine learning
The prosperity of machine learning has been accompanied by increasing attacks on the
training process. Among them, poisoning attacks have become an emerging threat during …
training process. Among them, poisoning attacks have become an emerging threat during …
Interpretable machine learning for knowledge generation in heterogeneous catalysis
Most applications of machine learning in heterogeneous catalysis thus far have used black-
box models to predict computable physical properties (descriptors), such as adsorption or …
box models to predict computable physical properties (descriptors), such as adsorption or …
Unified contrastive learning in image-text-label space
Visual recognition is recently learned via either supervised learning on human-annotated
image-label data or language-image contrastive learning with webly-crawled image-text …
image-label data or language-image contrastive learning with webly-crawled image-text …
Combustion machine learning: Principles, progress and prospects
Progress in combustion science and engineering has led to the generation of large amounts
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …
of data from large-scale simulations, high-resolution experiments, and sensors. This corpus …
Social interactions for autonomous driving: A review and perspectives
No human drives a car in a vacuum; she/he must negotiate with other road users to achieve
their goals in social traffic scenes. A rational human driver can interact with other road users …
their goals in social traffic scenes. A rational human driver can interact with other road users …