Plant Disease Detection Using Hyperspectral Imaging. - Peyman Moghadam; Daniel Ward; Ethan Goan; Srimal Jayawardena; Pavan Sikka; Emili Hernández (DICTA, 2017)

Deep Leaf Segmentation Using Synthetic Data. - Daniel Ward; Peyman Moghadam; Nicolas Hudson (BMVC, 2018)

PrimedRPA: primer design for recombinase polymerase amplification assays. - Matthew Higgins; Matt Ravenhall; Daniel Ward; Jody Phelan; Amy Ibrahim; Matthew S. Forrest; Taane G. Clark; Susana G. Campino (Bioinform., 2019)

Learning Arbitrary-Goal Fabric Folding with One Hour of Real Robot Experience. - Robert Lee; Daniel Ward; Vibhavari Dasagi; Akansel Cosgun; Juxi Leitner; Peter Corke (CoRL, 2020)

Temporally Coherent Embeddings for Self-Supervised Video Representation Learning. - Joshua Knights; Ben Harwood; Daniel Ward; Anthony Vanderkop; Olivia Mackenzie-Ross; Peyman Moghadam (ICPR, 2020)

Temporally Coherent Embeddings for Self-Supervised Video Representation Learning. - Joshua Knights; Anthony Vanderkop; Daniel Ward; Olivia Mackenzie-Ross; Peyman Moghadam (CoRR, 2020)

Scalable learning for bridging the species gap in image-based plant phenotyping. - Daniel Ward; Peyman Moghadam (Comput. Vis. Image Underst., 2020)

Robust Neural Posterior Estimation and Statistical Model Criticism. - Daniel Ward; Patrick Cannon; Mark Beaumont; Matteo Fasiolo; Sebastian M. Schmon (NeurIPS, 2022)

Investigating the Impact of Model Misspecification in Neural Simulation-based Inference. - Patrick Cannon; Daniel Ward; Sebastian M. Schmon (CoRR, 2022)

COVID-profiler: a webserver for the analysis of SARS-CoV-2 sequencing data. - Jody Phelan; Wouter Deelder; Daniel Ward; Susana G. Campino; Martin L. Hibberd; Taane G. Clark (BMC Bioinform., 2022)

The Hyperfitting Phenomenon: Sharpening and Stabilizing LLMs for Open-Ended Text Generation. - Fredrik Carlsson; Fangyu Liu 001; Daniel Ward; Murathan Kurfali; Joakim Nivre (ICLR, 2025)

SoftCVI: Contrastive variational inference with self-generated soft labels. - Daniel Ward; Mark Beaumont; Matteo Fasiolo (ICLR, 2025)