Kolmogorov-Arnold networks bridge AI and scientific discovery by increasing interpretability

AI has successfully been applied in many areas of science, advancing technologies like weather prediction and protein folding ...
eLife

Human EEG and artificial neural networks reveal disentangled representations and processing timelines of object real-world size and depth in natural images

Neural and computational evidence reveals that real-world size is a temporally late, semantically grounded, and hierarchically stable dimension of object representation in both human brains and ...
IEEE

Efficient Group Cosine Convolutional Neural Network for EEG-Based Seizure Identification

Abstract: Epilepsy is a common neurological disease, and its diagnosis usually depends on labor-intensive visual inspection of electroencephalogram (EEG). Although various deep learning-based seizure ...
IEEE

V-DCRNN: Virtual Network-Based Diffusion Convolutional Recurrent Neural Network for Estimating Unobserved Traffic Data

Abstract: Several studies have analyzed traffic patterns using Vehicle Detector (VD) and Global Positioning System (GPS) data. VD records the speed of vehicles passing through detectors, GPS data ...

Interpretable neural networks help reveal the nature of dark matter

A research team from the Xinjiang Astronomical Observatory (XAO) of the Chinese Academy of Sciences has developed an ...

OpenAI’s new ChatGPT image generator makes faking photos easy

For most of photography’s roughly 200-year history, altering a photo convincingly required either a darkroom, some Photoshop ...
Tech Xplore on MSN

Flexible position encoding helps LLMs follow complex instructions and shifting states

Most languages use word position and sentence structure to extract meaning. For example, "The cat sat on the box," is not the ...