A Northwestern Medicine study has shed light on one of the most intricate construction projects in biology: how cells build ...
A research team led by Professor Wang Hongzhi from the Hefei Institute of Physical Science of the Chinese Academy of Sciences has developed a multi-stage, dual-domain, progressive network with ...
Abstract: In this letter, we propose a meta-learning-based fast adversarial training method to address the vulnerability of graph neural network (GNN) based resource allocation method to adversarial ...
Intelligent Systems course project (MSc in Computer Engineering @ Unversity of Pisa). Design and development of a MLP, RBF networks and Fuzzy System to estimate person's affective state. Design, ...
Abstract: Training neural networks (NNs) to behave as model predictive control (MPC) algorithms is an effective way to implement them in constrained embedded devices. By collecting large amounts of ...
This blog post is the second in our Neural Super Sampling (NSS) series. The post explores why we introduced NSS and explains its architecture, training, and inference components. In August 2025, we ...
Artificial intelligence is now part of our daily lives, with the subsequent pressing need for larger, more complex models. However, the demand for ever-increasing power and computing capacity is ...
A new machine learning approach that draws inspiration from the way the human brain seems to model and learn about the world has proven capable of mastering a number of simple video games with ...
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