Spiking neural networks (SNNs) mirror the inherently event-driven way information is processed in the human brain by encoding it into the timing of spikes. In the field of event-based sensing, ...

This tutorial was designed for easily diving into TensorFlow, through examples. For readability, it includes both notebooks and source codes with explanation, for both TF v1 & v2. Some examples ...

This tutorial tries to do what most Most Machine Learning tutorials available online do not. It is not a 30 minute tutorial which teaches you how to "Train your own neural network" or "Learn deep ...

GPT (Generative Pre-trained Transformer) models, developed by OpenAI, are pre-trained language models specifically designed for text generation. These models can generate highly coherent, contextually ...

In the last few years, rapid progress has been unfolding in machine learning (ML) due to the release of specialized datasets that serve as experimental testbeds and public benchmarks, thus focusing ...

Autoplotter is an open-source Python library designed for Exploratory Data Analysis using a user-friendly Graphical User Interface. The library is built on the Dash framework, allowing users to create ...

Application of deep convolutional spiking neural networks (SNNs) to artificial intelligence (AI) tasks has recently gained a lot of interest since SNNs are hardware-friendly and energy-efficient.

Since its inception in 2014 by Goodfellow et al, generative adversarial networks (GANs) have taken the research community by storm. The business for improving GANs has grown to a point where papers on ...