Recurrent Graph Tensor Networks. - Yao Lei Xu; Danilo P. Mandic (CoRR, 2020)

Multi-Graph Tensor Networks. - Yao Lei Xu; Kriton Konstantinidis; Danilo P. Mandic (CoRR, 2020)

Recurrent Graph Tensor Networks: A Low-Complexity Framework for Modelling High-Dimensional Multi-Way Sequences. - Yao Lei Xu; Danilo P. Mandic (EUSIPCO, 2021)

Graph Theory for Metro Traffic Modelling. - Bruno Scalzo Dees; Yao Lei Xu; Anthony G. Constantinides; Danilo P. Mandic (IJCNN, 2021)

Tensor-Train Recurrent Neural Networks for Interpretable Multi-Way Financial Forecasting. - Yao Lei Xu; Giuseppe Giovanni Calvi; Danilo P. Mandic (IJCNN, 2021)

Tensor Networks for Multi-Modal Non-Euclidean Data. - Yao Lei Xu; Kriton Konstantinidis; Danilo P. Mandic (CoRR, 2021)

Reducing Computational Complexity of Tensor Contractions via Tensor-Train Networks. - Ilya Kisil; Giuseppe Giovanni Calvi; Kriton Konstantinidis; Yao Lei Xu; Danilo P. Mandic (CoRR, 2021)

Graph and tensor-train recurrent neural networks for high-dimensional models of limit order books. - Jacobo Roa-Vicens; Yao Lei Xu; Ricardo Silva 001; Danilo P. Mandic (ICAIF, 2022)

Variational Bayesian Tensor Networks with Structured Posteriors. - Kriton Konstantinidis; Yao Lei Xu; Qibin Zhao; Danilo P. Mandic (ICASSP, 2022)

Low-Complexity Attention Modelling via Graph Tensor Networks. - Yao Lei Xu; Kriton Konstantinidis; Shengxi Li; Ljubisa Stankovic; Danilo P. Mandic (ICASSP, 2022)

Graph-Regularized Tensor Regression: A Domain-Aware Framework for Interpretable Multi-Way Financial Modelling. - Yao Lei Xu; Kriton Konstantinidis; Danilo P. Mandic (CoRR, 2022)

Accelerating Tensor Contraction Products via Tensor-Train Decomposition [Tips & Tricks]. - Ilya Kisil; Giuseppe Giovanni Calvi; Kriton Konstantinidis; Yao Lei Xu; Danilo P. Mandic (IEEE Signal Process. Mag., 2022)

Hierarchical Graph Learning for Stock Market Prediction Via a Domain-Aware Graph Pooling Operator. - Arie N. Arya; Yao Lei Xu; Ljubisa Stankovic; Danilo P. Mandic (ICASSP, 2023)

Tensor Completion for Efficient and Accurate Hyperparameter Optimisation in Large-Scale Statistical Learning. - Aaman Rebello; Kriton Konstantinidis; Yao Lei Xu; Danilo P. Mandic (ICASSP, 2023)

Financial News Classification Model for NLP-based Bond Portfolio Construction. - Thanos Konstantinidis; Arnau Bonet Farres; Yao Lei Xu; Tony Constantinides; Danilo P. Mandic (DSP, 2023)

Text Mining for Sentiment Analysis in Bond Portfolio Construction. - Thanos Konstantinidis; Maya Golan; Yao Lei Xu; Tony Constantinides; Danilo P. Mandic (DSP, 2023)

A comparative study on ML-based approaches for Main Entity Detection in Financial Reports. - Thanos Konstantinidis; Yao Lei Xu; Tony Constantinides; Danilo P. Mandic (DSP, 2023)

Graph Tensor Networks: An Intuitive Framework for Designing Large-Scale Neural Learning Systems on Multiple Domains. - Yao Lei Xu; Kriton Konstantinidis; Danilo P. Mandic (CoRR, 2023)

TensorGPT: Efficient Compression of the Embedding Layer in LLMs based on the Tensor-Train Decomposition. - Mingxue Xu; Yao Lei Xu; Danilo P. Mandic (CoRR, 2023)

Graph-Regularized Tensor Regression: A Domain-Aware Framework for Interpretable Modeling of Multiway Data on Graphs. - Yao Lei Xu; Kriton Konstantinidis; Danilo P. Mandic (Neural Comput., 2023)

TensorSLM: Energy-efficient Embedding Compression of Sub-billion Parameter Language Models on Low-end Devices. - Mingxue Xu; Yao Lei Xu; Danilo P. Mandic (CoRR, 2025)