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2020 – today
- 2024
[i7]Daniel Ward, Mark Beaumont, Matteo Fasiolo:
SoftCVI: contrastive variational inference with self-generated soft labels. CoRR abs/2407.15687 (2024)- 2022
- [j3]Jody Phelan
, Wouter Deelder, Daniel Ward, Susana G. Campino, Martin L. Hibberd, Taane G. Clark:
COVID-profiler: a webserver for the analysis of SARS-CoV-2 sequencing data. BMC Bioinform. 23(1): 137 (2022) - [c5]Daniel Ward, Patrick Cannon, Mark Beaumont, Matteo Fasiolo, Sebastian M. Schmon:
Robust Neural Posterior Estimation and Statistical Model Criticism. NeurIPS 2022 - [i6]Patrick Cannon, Daniel Ward, Sebastian M. Schmon:
Investigating the Impact of Model Misspecification in Neural Simulation-based Inference. CoRR abs/2209.01845 (2022) - [i5]Daniel Ward, Patrick Cannon, Mark Beaumont, Matteo Fasiolo, Sebastian M. Schmon:
Robust Neural Posterior Estimation and Statistical Model Criticism. CoRR abs/2210.06564 (2022) - 2020
- [j2]Daniel Ward, Peyman Moghadam:
Scalable learning for bridging the species gap in image-based plant phenotyping. Comput. Vis. Image Underst. 197-198: 103009 (2020) - [c4]Robert Lee, Daniel Ward, Vibhavari Dasagi, Akansel Cosgun, Juxi Leitner, Peter Corke:
Learning Arbitrary-Goal Fabric Folding with One Hour of Real Robot Experience. CoRL 2020: 2317-2327 - [c3]Joshua Knights, Ben Harwood, Daniel Ward, Anthony Vanderkop, Olivia Mackenzie-Ross, Peyman Moghadam:
Temporally Coherent Embeddings for Self-Supervised Video Representation Learning. ICPR 2020: 8914-8921 - [i4]Daniel Ward, Peyman Moghadam:
Scalable learning for bridging the species gap in image-based plant phenotyping. CoRR abs/2003.10757 (2020) - [i3]Joshua Knights, Anthony Vanderkop, Daniel Ward, Olivia Mackenzie-Ross, Peyman Moghadam:
Temporally Coherent Embeddings for Self-Supervised Video Representation Learning. CoRR abs/2004.02753 (2020) - [i2]Robert Lee, Daniel Ward, Akansel Cosgun, Vibhavari Dasagi, Peter Corke, Jürgen Leitner:
Learning Arbitrary-Goal Fabric Folding with One Hour of Real Robot Experience. CoRR abs/2010.03209 (2020)
2010 – 2019
- 2019
- [j1]Matthew Higgins, Matt Ravenhall, Daniel Ward, Jody Phelan, Amy Ibrahim, Matthew S. Forrest, Taane G. Clark, Susana G. Campino:
PrimedRPA: primer design for recombinase polymerase amplification assays. Bioinform. 35(4): 682-684 (2019) - 2018
- [c2]Daniel Ward, Peyman Moghadam, Nicolas Hudson:
Deep Leaf Segmentation Using Synthetic Data. BMVC 2018: 327 - [i1]Daniel Ward, Peyman Moghadam, Nicolas Hudson:
Deep Leaf Segmentation Using Synthetic Data. CoRR abs/1807.10931 (2018) - 2017
- [c1]Peyman Moghadam, Daniel Ward, Ethan Goan, Srimal Jayawardena, Pavan Sikka, Emili Hernández:
Plant Disease Detection Using Hyperspectral Imaging. DICTA 2017: 1-8
Coauthor Index
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