Browsing: Networks

Backpropagation dominates deep learning, yet it uses a mechanism the brain likely cannot. Specifically, the backward pass needs exact transposes of forward weight matrices. This is…

One of the most utilized econometric workflows in the last decade has been that of using vector autoregressive models. From research done by academicians to economists…

about the latest technologies like large language models, Agentic AI, multimodal systems, and techniques like RAG. What are these technologies actually? How are they built? I…

poi_gdf[“cx”] = poi_gdf.geometry.x poi_gdf[“cy”] = poi_gdf.geometry.y coords = poi_gdf[[“cx”, “cy”]].to_numpy() nn = NearestNeighbors(radius=150.0).fit(coords) poi_gdf[“local_density”] = [len(idx) – 1 for idx in nn.radius_neighbors(coords, return_distance=False)] if segments_gdf is…

explanations begin with prediction. A churn model estimates whether a customer is likely to leave. A fraud model estimates whether a transaction is suspicious. A diagnosis…

by Conor Rowan and Finn Murphy-Blanchard Introduction with complex tasks such as image classification [1], autonomy [2], and language modeling [3], neural networks are spectacularly good…

Researchers from Sakana AI and the University of Tokyo propose DiffusionBlocks. It trains transformer-based networks one block at a time. Training memory is reduced by a…

has been in production two months. Accuracy is 92.9%. Then transaction patterns shift quietly. By the time your dashboard turns red, accuracy has collapsed to 44.6%.…

Governments introduce voluntary principles to secure 6G networks before commercial deployment beginsEarly planning emphasizes embedding cybersecurity protections into network design from the startAI tools are expected…

Abstract datasets are extremely imbalanced, with positive rates below 0.2%. Standard neural networks trained with weighted binary cross-entropy often achieve high ROC-AUC but struggle to identify…