Centrality and Composition of Four-Node Motifs in Metabolic Networks. - Mahendra Piraveenan; Kishan Wimalawarne; Dharshana Kasthurirathna (ICCS, 2013)

Multitask learning meets tensor factorization: task imputation via convex optimization. - Kishan Wimalawarne; Masashi Sugiyama; Ryota Tomioka (NIPS, 2014)

Theoretical and Experimental Analyses of Tensor-Based Regression and Classification. - Kishan Wimalawarne; Ryota Tomioka; Masashi Sugiyama (Neural Comput., 2016)

Convex Factorization Machine for Toxicogenomics Prediction. - Makoto Yamada; Wenzhao Lian; Amit Goyal 001; Jianhui Chen; Kishan Wimalawarne; Suleiman A. Khan; Samuel Kaski; Hiroshi Mamitsuka; Yi Chang 001 (KDD, 2017)

Efficient Convex Completion of Coupled Tensors using Coupled Nuclear Norms. - Kishan Wimalawarne; Hiroshi Mamitsuka (NeurIPS, 2018)

Convex Coupled Matrix and Tensor Completion. - Kishan Wimalawarne; Makoto Yamada; Hiroshi Mamitsuka (Neural Comput., 2018)

Scaled Coupled Norms and Coupled Higher-Order Tensor Completion. - Kishan Wimalawarne; Makoto Yamada; Hiroshi Mamitsuka (Neural Comput., 2020)

Adaptive and Interpretable Graph Convolution Networks Using Generalized Pagerank. - Kishan Wimalawarne; Taiji Suzuki (CoRR, 2021)

Reshaped tensor nuclear norms for higher order tensor completion. - Kishan Wimalawarne; Hiroshi Mamitsuka (Mach. Learn., 2021)

Layer-wise Adaptive Graph Convolution Networks Using Generalized Pagerank. - Kishan Wimalawarne; Taiji Suzuki (ACML, 2022)

Graph Polynomial Convolution Models for Node Classification of Non-Homophilous Graphs. - Kishan Wimalawarne; Taiji Suzuki (CoRR, 2022)

Learning Green's Function Efficiently Using Low-Rank Approximations. - Kishan Wimalawarne; Taiji Suzuki; Sophie Langer (CoRR, 2023)

Graph Polynomial Convolution Models for Node Classification of Non-Homophilous Graphs. - Kishan Wimalawarne; Taro Sawaki; Motokiyo Hirayama; Takanobu Kawahara; Taiji Suzuki (ICMLA, 2024)

Towards Green AI: Current status and future research. - Christian Clemm; Lutz Stobbe; Kishan Wimalawarne; Jan Druschke (CoRR, 2024)