Dispatches from the edge of chaos — on nonlinear dynamics, AI, emergence, and the mathematics of complex systems.
MobileNet and EfficientNet are efficiency-focused CNN architectures designed for deployment on mobile devices and edge hardware, achieving strong accuracy with dramatically fewer parameters and computations than
The Convolutional Neural Network (CNN) is the foundational architecture for computer vision, using learnable spatial filters to automatically extract hierarchical visual features from images, from low-level
WaveNet is a deep generative model for raw audio waveforms that uses dilated causal convolutions to model long-range temporal dependencies, producing remarkably natural-sounding speech and revolutionizing
U-Net is an encoder-decoder architecture with skip connections designed for biomedical image segmentation, producing pixel-precise segmentation masks by combining high-level semantic features with fine-grained spatial details.
ResNet (Residual Networks) and DenseNet (Densely Connected Networks) are landmark CNN architectures that solved the degradation problem in deep networks through skip connections, enabling training of