deep-learning

deep-learning Editors Pick

How to Build Memory-Efficient Transformers with xFormers Using Packed Sequences, GQA, ALiBi, SwiGLU, and Causal Attention
ByRicardo June 17, 2026June 17, 2026

In this tutorial, we implement xFormers: a sensible toolkit for constructing quick, memory-efficient Transformer fashions on GPUs. We start by validating memory-efficient consideration towards an ordinary consideration implementation, then examine their pace and reminiscence consumption throughout totally different sequence lengths. We then look at causal masking, packed variable-length sequences, grouped-query consideration, and customized ALiBi positional…

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Artificial Intelligence deep-learning

A Coding Implementation of End-to-End Brain Decoding from MEG Signals Using NeuralSet and Deep Learning for Predicting Linguistic Features
ByRicardo May 2, 2026

In this tutorial, we discover how we are able to decode linguistic options straight from mind indicators utilizing a contemporary neuroAI pipeline. We work with MEG information and construct an end-to-end system that transforms uncooked neural exercise into significant predictions, on this case, estimating phrase size from mind responses. We arrange the atmosphere, load and…

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Artificial Intelligence deep-learning

A Detailed Implementation on Equinox with JAX Native Modules, Filtered Transforms, Stateful Layers, and End-to-End Training Workflows
ByRicardo April 22, 2026

In this tutorial, we discover Equinox, a light-weight and elegant neural community library constructed on JAX, and present learn how to use it. We start by understanding how eqx.Module treats fashions as PyTrees, which makes parameter dealing with, transformation, and serialization really feel easy and express. As we transfer ahead, we work by way of…

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Artificial Intelligence deep-learning

A Step-by-Step Coding Tutorial on NVIDIA PhysicsNeMo: Darcy Flow, FNOs, PINNs, Surrogate Models, and Inference Benchmarking
ByRicardo April 13, 2026

In this tutorial, we implement NVIDIA PhysicsNeMo on Colab and construct a sensible workflow for physics-informed machine studying. We begin by organising the setting, producing information for the 2D Darcy Flow drawback, and visualizing the bodily fields to obviously perceive the educational job. From there, we implement and practice highly effective fashions such because the…

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Artificial Intelligence deep-learning

Meet SymTorch: A PyTorch Library that Translates Deep Learning Models into Human-Readable Equations
ByRicardo March 4, 2026

Can symbolic regression be the key to transforming opaque deep learning models into interpretable, closed-form mathematical equations? or Say you have trained your deep learning model. It works. But do you know what it has actually learned? A team of University of Cambridge researchers propose ‘SymTorch’, a library designed to integrate symbolic regression (SR) into…

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deep-learning Editors Pick

How to Design Complex Deep Learning Tensor Pipelines Using Einops with Vision, Attention, and Multimodal Examples
ByRicardo February 12, 2026

In this tutorial, we walk through advanced usage of Einops to express complex tensor transformations in a clear, readable, and mathematically precise way. We demonstrate how rearrange, reduce, repeat, einsum, and pack/unpack let us reshape, aggregate, and combine tensors without relying on error-prone manual dimension handling. We focus on real deep-learning patterns, such as vision…

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Artificial Intelligence deep-learning

A Coding Guide to Demonstrate Targeted Data Poisoning Attacks in Deep Learning by Label Flipping on CIFAR-10 with PyTorch
ByRicardo January 11, 2026

In this tutorial, we demonstrate a realistic data poisoning attack by manipulating labels in the CIFAR-10 dataset and observing its impact on model behavior. We construct a clean and a poisoned training pipeline side by side, using a ResNet-style convolutional network to ensure stable, comparable learning dynamics. By selectively flipping a fraction of samples from…

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deep-learning Videos

Challenges & advances of deep learning in digital pathology
ByRicardo November 3, 2025

Learn extra Enjoyed this video? Why not take a look at some associated studying 👇

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Artificial Intelligence deep-learning

Deep Learning Framework Showdown: PyTorch vs TensorFlow in 2025
ByRicardo August 21, 2025August 21, 2025

The selection between PyTorch and TensorFlow stays probably the most debated selections in AI improvement. Each frameworks have developed dramatically since their inception, converging in some areas whereas sustaining distinct strengths. This text explores the most recent patterns from the great survey paper from Alfaisal College, Saudi Arabia, synthesizing usability, efficiency, deployment, and ecosystem concerns…

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AI deep-learning

Mixture of Experts — Scaling AI Models with Efficiency and Flexibility
ByRicardo July 18, 2025

This article draws insights from the paper ‘Mixture of Experts in Large Language Models’ (arXiv:2507.11181), examining how MoE… Continue reading on Artificial Intelligence in Plain English »

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deep-learning

How to Build Memory-Efficient Transformers with xFormers Using Packed Sequences, GQA, ALiBi, SwiGLU, and Causal Attention

A Coding Implementation of End-to-End Brain Decoding from MEG Signals Using NeuralSet and Deep Learning for Predicting Linguistic Features

A Detailed Implementation on Equinox with JAX Native Modules, Filtered Transforms, Stateful Layers, and End-to-End Training Workflows

A Step-by-Step Coding Tutorial on NVIDIA PhysicsNeMo: Darcy Flow, FNOs, PINNs, Surrogate Models, and Inference Benchmarking

Meet SymTorch: A PyTorch Library that Translates Deep Learning Models into Human-Readable Equations

How to Design Complex Deep Learning Tensor Pipelines Using Einops with Vision, Attention, and Multimodal Examples

A Coding Guide to Demonstrate Targeted Data Poisoning Attacks in Deep Learning by Label Flipping on CIFAR-10 with PyTorch

Challenges & advances of deep learning in digital pathology

Deep Learning Framework Showdown: PyTorch vs TensorFlow in 2025

Mixture of Experts — Scaling AI Models with Efficiency and Flexibility

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