output
20212026
most citedA Knowledge Graph-Enhanced Tensor Factorisation Model for Discovering Drug Targets

14 citations

researchers with a paper here

Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.

collaborating institutions

7 papers

cs.CV2026

Adversarial Batch Representation Augmentation for Batch Correction in High-Content Cellular Screening

Lei Tong, Xujing Yao, Adam Corrigan +6

High-Content Screening routinely generates massive volumes of cell painting images for phenotypic profiling. However, technical variations across experimental executions inevitably…

stat.ML2025

Gradient-Guided Furthest Point Sampling for Robust Training Set Selection

Morris Trestman, Stefan Gugler, Felix A. Faber +1

Training set sampling methods are used to improve model performance and lower data costs in machine learning problems relevant to chemistry. We introduce Gradient Guided Furthest P…

cs.LG2025★ 1 cited

Scalable Unit Harmonization in Medical Informatics via Bayesian-Optimized Retrieval and Transformer-Based Re-ranking

Jordi de la Torre

Objective: To develop and evaluate a scalable methodology for harmonizing inconsistent units in large-scale clinical datasets, addressing a key barrier to data interoperability. Ma…

cs.LG2024★ 2 cited

The Role of Graph Topology in the Performance of Biomedical Knowledge Graph Completion Models

Alberto Cattaneo, Stephen Bonner, Thomas Martynec +4

Knowledge Graph Completion has been increasingly adopted as a useful method for helping address several tasks in biomedical research, such as drug repurposing or drug-target identi…

stat.CO2024★ 1 cited

Potential outcome simulation for efficient head-to-head comparison of adaptive dose-finding designs

Michael Sweeting, Daniel Slade, Dan Jackson +1

Dose-finding trials are a key component of the drug development process and rely on a statistical design to help inform dosing decisions. Triallists wishing to choose a design requ…

cs.SD2021★ 4 cited

Towards Robust Waveform-Based Acoustic Models

Dino Oglic, Zoran Cvetkovic, Peter Sollich +2

We study the problem of learning robust acoustic models in adverse environments, characterized by a significant mismatch between training and test conditions. This problem is of pa…

q-bio.QM2021★ 14 cited

A Knowledge Graph-Enhanced Tensor Factorisation Model for Discovering Drug Targets

Cheng Ye, Rowan Swiers, Stephen Bonner +1

The drug discovery and development process is a long and expensive one, costing over 1 billion USD on average per drug and taking 10-15 years. To reduce the high levels of attritio…