Abstract: In recent years, neural network models have been widely used in many tasks, however, tampering operations from malicious attackers, e.g., backdoor attacks and parameter malicious tampering, ...

Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...

As a result, the on-chip learning-based neuromorphic system achieved up to 20,000 times faster processing speed while maintaining similar interpretation accuracy to existing conventional techniques.

Learn how Network in Network (NiN) architectures work and how to implement them using PyTorch. This tutorial covers the concept, benefits, and step-by-step coding examples to help you build better ...

Calling the model on the input returns a 2-dimensional tensor with dim=0 corresponding to each output of 10 raw predicted values for each class, and dim=1 corresponding to the individual values of ...

Apple has announced its latest M5 chipset with the next-gen GPU that brings a Neural Accelerator into each GPU core. The Apple M5 features a 10-core GPU, up to 10 CPU cores, a 16-core Neural Engine, ...

Abstract: Delivering realistic, real-time virtual experiences in the Metaverse demands computationally intensive rendering tasks with strict latency constraints. These challenges are further ...

The brain criticality hypothesis has been a central research topic in theoretical neuroscience for two decades. This hypothesis suggests that the brain operates near the critical point at the boundary ...

The integration of neural network models in autonomous robotics represents a monumental leap in artificial intelligence and robotics. These models, mirroring the human brain's complexity and ...

This study presents useful findings on the differences between male and hermaphrodite C. elegans connectomes and how they may result in changes in locomotory behavioural outputs. However, the study ...