How data symmetry informs neural network architectures

A smarter way to cluster data using deep learning

A PyTorch implementation on the ConvNeXt architecture

Introduction The vanilla ViT is problematic. If you take a look at the original ViT paper [1], you’ll notice that although this deep learning model proved to work extremely well, it requires hundreds…

After dispatching its Ghost Dragon ISR quadcopters to Ukraine in mid-2022, Estonian startup KrattWorks quickly realized the need for continuous innovation due to rapid advances in electronic warfare.…

Imagine treating inflammation with sound waves instead of pills. Learn how focused ultrasound stimulation is changing the approach to chronic diseases.

RAG quality for AI agents is critical, and traditional keyword-based search engines consistently underperform in agentic or multi-step tasks, where semantic grounding and contextual nuance matter most.

In this talk, Will Bryk, CEO of Exa will live code two…

Solving the Heat Equation using DeepXDE. The post Physics-Informed Neural Networks for Inverse PDE Problems appeared first on Towards Data Science. Generated by RSStT. The copyright belongs to the original author. Source

Practical Neuroevolution: Reproducing NEAT’s Innovations and Code Walkthrough The post From Genes to Neural Networks: Understanding and Building NEAT (Neuro-Evolution of Augmenting Topologies) from Scratch appeared first on Towards Data Science. Generated…

A walk-through of and the maths behind using low-capacity networks to acquire fine-grained scoring when only categorical labelling is available for training. We use it to predict the severity of an infection on a scale based on information on just rough outcomes…