The article presents Clifford-Steerable Convolutional Neural Networks (CS-CNNs), a new class of E(p, q)-equivariant CNNs. These networks process multivector fields on pseudo-Euclidean spaces Rp,q, offering significant improvements over baseline methods…
Continue readingThe study introduces MAIDCRL (Multi-Agent Dense-CNN Reinforcement Learning), a reinforcement learning algorithm that incorporates convolutional layers into the deep model architecture for better multi-agent control in StarCraft Multi-Agent Challenge scenarios….
Continue readingThe article discusses the use of Raman Spectroscopy in biotechnology as a process analytical technology. It focuses on the use of Convolutional Neural Networks (CNNs) for handling non-Gaussian noise and…
Continue readingThis research uses a Convolutional Neural Network (CNN) to predict bail judgements in India’s legal system, with a focus on Hindi legal documents. The study identifies a lack of machine…
Continue readingThis paper focuses on the development of a new tool, ViSual_IceD, a convolutional neural network (CNN) for improved sea ice detection. This tool builds upon the classic U-Net architecture and…
Continue readingThe study explores invariance in neural networks, a feature necessary for many tasks. The authors propose measures to quantify the invariance of neural networks in terms of their internal representation….
Continue readingThe research introduces a novel approach in circuit design by using artificial intelligence technologies. The most time-consuming parts of the physical design process are placement and routing. This research proposes…
Continue readingThis research paper introduces a U-Net-based network that uses spatio-temporal features with cross-attention transformers to extract information from historical maps. This method addresses the challenges of data-dependent uncertainty in the…
Continue readingThe paper presents an intriguing phenomenon – the successful reconstruction of images using a set of one-way wave equations with hidden and learnable speeds. Each image corresponds to a unique…
Continue readingThis paper presents a study on automatic performer identification in expressive piano performances using Convolutional Neural Networks (CNNs) and expressive features. The study addresses the task of identifying virtuoso pianists,…
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