Spiking neural networks (SNNs) offer a promising energy-efficient alternative to artificial neural networks (ANNs), in virtue of their high biological plausibility, rich spatial-temporal dynamics, and ...

You can create a release to package software, along with release notes and links to binary files, for other people to use. Learn more about releases in our docs.

Predict dynamic behaviors in a physics system in a way that's computationally efficient and adaptable to a range of scenarios.

A PyG re-implementation of NBFNet can be found here. You may install the dependencies via either conda or pip. Generally, NBFNet works with Python 3.7/3.8 and PyTorch ...

that are learnable by a geometric neural network. In experiments on macaque and rat brain recordings, the scientists used MARBLE to show that when different animals used the same mental strategy to ...

Unlike traditional electron microscopy, which only visualizes synapses, this method also measures connection strength, providing deeper insight into brain network function. The chip mimics patch-clamp ...

The pair tested their approach on the Abstraction and Reasoning Corpus (ARC-AGI), an unbeaten visual benchmark created in 2019 by machine-learning researcher François Chollet to test AI systems' ...

AI servers are used for training and deploying machine learning models, executing neural networks for tasks like image and speech recognition, analyzing and understanding human language ...