5 papers
TGB 2.0: A Benchmark for Learning on Temporal Knowledge Graphs and Heterogeneous Graphs
Julia Gastinger, Shenyang Huang, Mikhail Galkin +9
Multi-relational temporal graphs are powerful tools for modeling real-world data, capturing the evolving and interconnected nature of entities over time. Recently, many novel model…
Resource-constrained knowledge diffusion processes inspired by human peer learning
Ehsan Beikihassan, Amy K. Hoover, Ioannis Koutis +2
We consider a setting where a population of artificial learners is given, and the objective is to optimize aggregate measures of performance, under constraints on training resource…
Towards Foundational Models for Molecular Learning on Large-Scale Multi-Task Datasets
Dominique Beaini, Shenyang Huang, Joao Alex Cunha +32
Recently, pre-trained foundation models have enabled significant advancements in multiple fields. In molecular machine learning, however, where datasets are often hand-curated, and…
Sidestepping Barriers for Dominating Set in Parameterized Complexity
Ioannis Koutis, Michał Włodarczyk, Meirav Zehavi
We study the classic {\sc Dominating Set} problem with respect to several prominent parameters. Specifically, we present algorithmic results that sidestep time complexity barriers…
SGC: A semi-supervised pipeline for gene clustering using self-training approach in gene co-expression networks
Niloofar Aghaieabiane, Ioannis Koutis
A widely used approach for extracting information from gene expression data employ the construction of a gene co-expression network and the subsequent application of algorithms tha…