Network Programming
Network programming focuses on designing and implementing algorithms and architectures for processing information across interconnected nodes, aiming to efficiently solve complex computational problems. Current research emphasizes developing novel network architectures, such as graph neural networks and deep operator networks, and improving existing algorithms through techniques like frequency domain inference and tensor decomposition for faster and more accurate computations. These advancements are significant for diverse applications, including improved recommendation systems, enhanced anomaly detection in network flows, and more accurate causal inference from network data. The field's impact spans various scientific disciplines and practical applications, driving progress in areas like machine learning, signal processing, and social network analysis.
Papers
MsMorph: An Unsupervised pyramid learning network for brain image registration
Jiaofen Nan, Gaodeng Fan, Kaifan Zhang, Chen Zhao, Fubao Zhu, Weihua Zhou
Melody Construction for Persian lyrics using LSTM recurrent neural networks
Farshad Jafari, Farzad Didehvar, Amin Gheibi
CASCRNet: An Atrous Spatial Pyramid Pooling and Shared Channel Residual based Network for Capsule Endoscopy
K V Srinanda, M Manvith Prabhu, Shyam Lal
Mechanisms of Symbol Processing for In-Context Learning in Transformer Networks
Paul Smolensky, Roland Fernandez, Zhenghao Herbert Zhou, Mattia Opper, Jianfeng Gao
Hierarchical Multi-agent Reinforcement Learning for Cyber Network Defense
Aditya Vikram Singh, Ethan Rathbun, Emma Graham, Lisa Oakley, Simona Boboila, Alina Oprea, Peter Chin
Resource-Efficient Sensor Fusion via System-Wide Dynamic Gated Neural Networks
Chetna Singhal, Yashuo Wu, Francesco Malandrino, Sharon Ladron de Guevara Contreras, Marco Levorato, Carla Fabiana Chiasserini
CFTS-GAN: Continual Few-Shot Teacher Student for Generative Adversarial Networks
Munsif Ali, Leonardo Rossi, Massimo Bertozzi
Fairness-Enhancing Ensemble Classification in Water Distribution Networks
Janine Strotherm, Barbara Hammer
Latent Image and Video Resolution Prediction using Convolutional Neural Networks
Rittwika Kansabanik, Adrian Barbu
BeniFul: Backdoor Defense via Middle Feature Analysis for Deep Neural Networks
Xinfu Li, Junying Zhang, Xindi Ma
Implementing Derivations of Definite Logic Programs with Self-Attention Networks
Phan Thi Thanh Thuy, Akihiro Yamamoto
Advancing the Understanding of Fixed Point Iterations in Deep Neural Networks: A Detailed Analytical Study
Yekun Ke, Xiaoyu Li, Yingyu Liang, Zhenmei Shi, Zhao Song
A Scalable Communication Protocol for Networks of Large Language Models
Samuele Marro, Emanuele La Malfa, Jesse Wright, Guohao Li, Nigel Shadbolt, Michael Wooldridge, Philip Torr
EasyRAG: Efficient Retrieval-Augmented Generation Framework for Automated Network Operations
Zhangchi Feng, Dongdong Kuang, Zhongyuan Wang, Zhijie Nie, Yaowei Zheng, Richong Zhang
Towards Bridging Generalization and Expressivity of Graph Neural Networks
Shouheng Li, Floris Geerts, Dongwoo Kim, Qing Wang