Active Learning of Transfer Relationships for Multiple Related Bayesian Network Structures. - Diane Oyen (ICDM Workshops, 2011)

Leveraging Domain Knowledge in Multitask Bayesian Network Structure Learning. - Diane Oyen; Terran Lane (AAAI, 2012)

Bayesian Discovery of Multiple Bayesian Networks via Transfer Learning. - Diane Oyen; Terran Lane (ICDM, 2013)

Controlling the Precision-Recall Tradeoff in Differential Dependency Network Analysis. - Diane Oyen; Alexandru Niculescu-Mizil; Rachel Ostroff; Alex Stewart; Vincent P. Clark (CoRR, 2013)

Discovering compositional trends in Mars rock targets from ChemCam spectroscopy and remote imaging. - Diane Oyen; Nina Lanza; Reid B. Porter (AIPR, 2015)

Learning Watershed Cuts Energy Functions. - Reid B. Porter; Diane Oyen; Beate G. Zimmer (ISMM, 2015)

Transfer learning for Bayesian discovery of multiple Bayesian networks. - Diane Oyen; Terran Lane (Knowl. Inf. Syst., 2015)

Bayesian Networks with Prior Knowledge for Malware Phylogenetics. - Diane Oyen; Blake Anderson; Christine M. Anderson-Cook (AAAI Workshop: Artificial Intelligence for Cyber Security, 2016)

Learning Planar Ising Models. - Jason K. Johnson; Diane Oyen; Michael Chertkov; Praneeth Netrapalli (J. Mach. Learn. Res., 2016)

Order priors for Bayesian network discovery with an application to malware phylogeny. - Diane Oyen; Blake Anderson; Kari Sentz; Christine M. Anderson-Cook (Stat. Anal. Data Min., 2017)

Quantum Algorithm Implementations for Beginners. - Patrick J. Coles; Stephan J. Eidenbenz; Scott Pakin; Adetokunbo Adedoyin; John Ambrosiano; Petr M. Anisimov; William Casper; Gopinath Chennupati; Carleton Coffrin; Hristo N. Djidjev; David Gunter; Satish Karra; et al. (CoRR, 2018)

A Novel Algorithm for Skeleton Extraction From Images Using Topological Graph Analysis. - Liping Yang 002; Diane Oyen; Brendt Wohlberg (CVPR Workshops, 2019)

A Topological Graph-Based Representation for Denoising Low Quality Binary Images. - Catherine Potts; Liping Yang 002; Diane Oyen; Brendt Wohlberg (ICCV Workshops, 2019)

Learning Diverse Gaussian Graphical Models and Interpreting Edges. - Roozbeh Yousefzadeh; Diane Oyen; Nina Lanza (SDM, 2019)

The ISTI Rapid Response on Exploring Cloud Computing 2018. - Carleton Coffrin; James Arnold; Stephan J. Eidenbenz; Derek Aberle; John Ambrosiano; Zachary K. Baker; Sara Brambilla; Michael J. Brown; K. Nolan Carter; Pinghan Chu; Patrick Conry; Keeley Costigan; et al. (CoRR, 2019)

Physics-Informed Spatiotemporal Deep Learning for Emulating Coupled Dynamical Systems. - Anishi Mehta; Cory Braker Scott; Diane Oyen; Nishant Panda; Gowri Srinivasan (AAAI Spring Symposium: MLPS, 2020)

Diagram Image Retrieval using Sketch-Based Deep Learning and Transfer Learning. - Manish Bhattarai; Diane Oyen; Juan Castorena; Liping Yang 002; Brendt Wohlberg (CVPR Workshops, 2020)

Learning Spatial Relationships between Samples of Patent Image Shapes. - Juan Castorena; Manish Bhattarai; Diane Oyen (CVPR Workshops, 2020)

Learning Shapes on Image Sampled Points with Dynamic Graph CNNs. - Juan Castorena; Diane Oyen (SSIAI, 2020)

TGGLines: A Robust Topological Graph Guided Line Segment Detector for Low Quality Binary Images. - Ming Gong; Liping Yang 002; Catherine Potts; Vijayan K. Asari; Diane Oyen; Brendt Wohlberg (CoRR, 2020)

StressNet: Deep Learning to Predict Stress With Fracture Propagation in Brittle Materials. - Yinan Wang; Diane Oyen; Weihong Guo 001; Anishi Mehta; Cory Braker Scott; Nishant Panda; M. Giselle Fernández-Godino; Gowri Srinivasan; Xiaowei Yue (CoRR, 2020)

Deep Spectral CNN for Laser Induced Breakdown Spectroscopy. - Juan Castorena; Diane Oyen; Ann Ollila; Carey Legget; Nina Lanza (CoRR, 2020)

Mesoscale informed parameter estimation through machine learning: A case-study in fracture modeling. - Nishant Panda; Dave Osthus; Gowri Srinivasan; Daniel O'Malley; Viet T. Chau; Diane Oyen; Humberto Godinez (J. Comput. Phys., 2020)

Recognizing Figure Labels in Patents. - Ming Gong; Xin Wei; Diane Oyen; Jian Wu 006; Martin Gryder; Liping Yang 002 (SDU@AAAI, 2021)

Fast Gaussian Process Estimation for Large-Scale In Situ Inference using Convolutional Neural Networks. - Divya Banesh; Nishant Panda; Ayan Biswas; Luke Van Roekel; Diane Oyen; Nathan M. Urban; Michael Grosskopf; Jonathan David Wolfe; Earl Lawrence (IEEE BigData, 2021)

Diff2Dist: Learning Spectrally Distinct Edge Functions, with Applications to Cell Morphology Analysis. - Cory Braker Scott; Eric Mjolsness; Diane Oyen; Chie Kodera; David Bouchez; Magalie Uyttewaal (CoRR, 2021)

Neural density estimation and uncertainty quantification for laser induced breakdown spectroscopy spectra. - Katiana Kontolati; Natalie Klein; Nishant Panda; Diane Oyen (CoRR, 2021)

Learning to Pre-process Laser Induced Breakdown Spectroscopy Signals Without Clean Data. - Juan Castorena; Diane Oyen (CoRR, 2021)

On visual self-supervision and its effect on model robustness. - Michal Kucer; Diane Oyen; Garrett T. Kenyon (CoRR, 2021)

Segmenting Technical Drawing Figures in US Patents. - Md Reshad Ul Hoque; Xin Wei; Muntabir Hasan Choudhury; Kehinde Ajayi; Martin Gryder; Jian Wu 006; Diane Oyen (SDU@AAAI, 2022)

Spectroscopynet: Learning to Pre-Process Spectroscopy Signals Without Clean Data. - Juan Castorena; Diane Oyen (IEEECONF, 2022)

Abstract Images Have Different Levels of Retrievability Per Reverse Image Search Engine. - Shawn M. Jones; Diane Oyen (ECCV Workshops (8), 2022)

Visual descriptor extraction from patent figure captions: a case study of data efficiency between BiLSTM and transformer. - Xin Wei; Jian Wu 006; Kehinde Ajayi; Diane Oyen (JCDL, 2022)

Robustness to Label Noise Depends on the Shape of the Noise Distribution. - Diane Oyen; Michal Kucer; Nicolas W. Hengartner; Har Simrat Singh (NeurIPS, 2022)

DeepPatent: Large scale patent drawing recognition and retrieval. - Michal Kucer; Diane Oyen; Juan Castorena; Jian Wu 006 (WACV, 2022)

Robustness to Label Noise Depends on the Shape of the Noise Distribution in Feature Space. - Diane Oyen; Michal Kucer; Nick Hengartner; Har Simrat Singh (CoRR, 2022)

Generative structured normalizing flow Gaussian processes applied to spectroscopic data. - Natalie Klein; Nishant Panda; Patrick Gasda; Diane Oyen (CoRR, 2022)

Discovering Image Usage Online: A Case Study with "Flatten the Curve". - Shawn M. Jones; Diane Oyen (JCDL, 2023)

Predicting Expressibility of Parameterized Quantum Circuits Using Graph Neural Network. - Shamminuj Aktar; Andreas Bärtschi; Abdel-Hameed A. Badawy; Diane Oyen; Stephan J. Eidenbenz (QCE, 2023)

Semi-supervised Learning of Pushforwards For Domain Translation & Adaptation. - Nishant Panda; Natalie Klein; Dominic Yang; Patrick Gasda; Diane Oyen (CoRR, 2023)

DeepPatent2: A Large-Scale Benchmarking Corpus for Technical Drawing Understanding. - Kehinde Ajayi; Xin Wei; Martin Gryder; Winston Shields; Jian Wu 006; Shawn M. Jones; Michal Kucer; Diane Oyen (CoRR, 2023)

Graph Neural Networks for Parameterized Quantum Circuits Expressibility Estimation. - Shamminuj Aktar; Andreas Bärtschi; Diane Oyen; Stephan J. Eidenbenz; Abdel-Hameed A. Badawy (QCE, 2024)