Neural Networks news and analysis on Web Pulse: 1261 curated articles tracking the latest Neural Networks developments, tools, and research, updated continuously from vetted sources.
A new study from arXiv (2607.09684v1) evaluating Scientific Machine Learning methods including Neural ODEs, PINNs, and UDEs across 23 countries finds that none of the models achieve consistently strong macroeconomic fore…
Researchers propose MVMGNN, a multi-view masked graph neural network for Alzheimer's disease diagnosis using structural MRI, which outperforms competing approaches on the ADNI dataset by jointly capturing spatial relatio…
A new comprehensive survey proposes a two-level taxonomy framework for graph neural network (GNN)-based knowledge graph technologies, covering the knowledge graph pipeline and GNN model perspectives. The study, published…
Researchers introduced WiCAT, a multi-subject model for widefield calcium imaging that uses self-supervised pretraining and atlas-grounded tokenization to outperform single-session models and achieve zero-shot behavior d…
A developer built a neural network that can be trained using finger gestures, enabling intuitive, hands-on machine learning without a keyboard or mouse. The system uses a webcam to track finger movements and adjusts mode…
A technical walkthrough demonstrates the arithmetic behind attention in GPT-2 by computing one token's contextual embedding from raw scores, showing that attention weights and values are produced by separate model compon…
A developer has built a complete, accelerated tensor library from scratch in C, inspired by Fabrice Bellard's libnc. The library implements tensors as flat arrays with shape and stride metadata, reference counting for sh…
Northwestern University engineers have developed a brain-inspired electronic device that detects anomalies with over 98% accuracy using roughly 10,000 times fewer computer operations than conventional AI, according to a …
A developer has built a Fashion-MNIST neural network trainer in pure SQL using xarray-sql, demonstrating that matrix multiplication and backpropagation can be expressed as joins and aggregations. The three-layer MLP with…
A developer implemented a neural network in SQL using the xarray_sql library, achieving a speedup of approximately 1.8x on Fashion-MNIST by skipping zero-valued pixels during layer-0 contraction. The project, shared on H…
A new research paper argues that deep learning algorithms fail to learn from unfiltered experience because they are designed for human-curated datasets. The authors demonstrate that standard optimizers like SGD and Adam …
Researchers are using neural networks to estimate measurement-induced entanglement (MIE) in quantum systems, revealing a learnability transition that marks the boundary between classically feasible and infeasible computa…
A new study from the University of Illinois Grainger College of Engineering challenges the traditional view that the brain makes decisions only after information passes through a strict hierarchy of regions. Led by elect…
A new AI-driven framework using a Transformer-empowered actor-critic design promises to revolutionize Virtualized Network Function management for 6G networks, outperforming existing solutions in service acceptance rates …
A new universal approximation theorem leveraging Leray-Schauder mappings and orthogonal projections in Banach spaces could reshape operator learning, providing a theoretical foundation for deep learning methodologies in …
Physicist Roger Penrose argues that consciousness cannot be produced by algorithmic computation and requires undiscovered physics, according to a Space Daily feature on his Orchestrated Objective Reduction (Orch-OR) theo…
Researchers have demonstrated a 128-qubit Quantum Convolutional Neural Network (QCNN) that achieves efficient image classification on the MNIST dataset without exponentially growing hardware demands. The QCNN uses a hier…
A new study on memory-managed long-context attention achieves a perfect 1.000 score on Track A, a controlled retrieval task, compared to a 0.333 baseline, and outperforms dense retrieval methods by up to 16.6 F1 points o…
Neural language models face a softmax bottleneck that limits both expressivity and optimization, with research showing 95-99% of gradient norm smothered by the output layer. The bottleneck makes trivial patterns unlearna…
A new framework called PHINN-EEG uses topological methods to enhance dream detection in EEG data, achieving AUC scores of 0.82-0.90 compared to the traditional 0.70 from spectral analyses. The approach, tested on 1,462 a…