Researchers at University of Southern California and University of Pennsylvania recently introduced a new nonlinear dynamical modeling framework based on recurrent neural networks (RNNs) that ...

Throughout their everyday lives, humans are typically required to make a wide range of decisions, which can impact their well ...

The next library you'll need is Pandas, which will let you import the dataset and view it in columns as a "data frame." It's ...

Rats exhibit significant recovery of locomotor function following incomplete spinal cord injuries, albeit with altered gait expression and reduced speed and stepping frequency. These changes likely ...

The rise of generative artificial intelligence (AI), particularly large language models (LLMs), has marked a transformative ...

Dynamic networks are used in a wide range of fields, including social network analysis, recommender systems and epidemiology. Representing complex networks as structures changing over time allow ...

Autonomous underwater vehicles (AUVs) have become important tools in the ocean exploration and have drawn considerable attention. Precise control for AUVs is the prerequisite to effectively execute ...

This is an extension of a demo at 14th Cellular Nanoscale Networks and Applications (CNNA) Conference 2014. I have written a blog post, available at Image Processing in CNN with Python on Raspberry Pi ...

Beyond the reported performance improvements, OpenAI announced a substantial price reduction for developers. O3-pro costs $20 ...

Both the inverse and forward renderers are video diffusion models trained on a combination of curated synthetic datasets and auto-labeled real-world videos. Unlike classic PBR, which relies on precise ...

What makes this development especially revolutionary in battery research is the integration of physics-informed principles into neural networks. Traditional neural networks are data-driven models that ...