Biological neural networks are immensely complex systems underlying all aspects of cognition and behavior. Despite significant advances in neuroscience, a ...

Machine learning models called convolutional neural networks (CNNs) power technologies like image recognition and language ...

This study presents a valuable tool named TSvelo, a computational framework for RNA velocity inference that models transcriptional regulation and gene-specific splicing. The evidence supporting the ...

In the development of modern animal husbandry, the feed industry serves as a crucial material foundation, and extrusion puffing technology has become ...

If you are also thinking of building a career in AI by taking an online course from home, then IIT Kharagpur is giving you a ...

Information Theory Meets Deep Neural Networks: Theory and Applications. The previous volume can be viewed here: Volume I Deep Neural Networks (DNNs) have become one of the most popular research ...

In our increasingly electrified world, supercapacitors have emerged as critical components in transportation and renewable energy systems, prized for their remarkable power density, cycling stability, ...

Abstract: Bayesian Neural Networks (BNNs) offer robust uncertainty estimation capabilities through probabilistic modeling, yet their prohibitively high computational complexity and resource ...

Gut bacteria are known to be a key factor in many health-related concerns. However, the number and variety of them is vast, as are the ways in which they interact with the body's chemistry and each ...

Gut bacteria are known to be a key factor in many health-related concerns. However, the number and variety of them is vast, as are the ways in which they interact with the body’s chemistry and each ...

Abstract: One of the most popular recent areas of machine learning predicates the use of neural networks (NNs) augmented by information about the underlying process in the form of partial differential ...