Anj Simmons

According to our database, Anj Simmons authored at least 27 papers between 2015 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Comparative analysis of real issues in open-source machine learning projects.

Tuan Dung Lai, Anj Simmons, Scott Barnett, Jean-Guy Schneider, Rajesh Vasa

Empir. Softw. Eng., May, 2024

Minimising changes to audit when updating decision trees.

Anj Simmons, Scott Barnett, Anupam Chaudhuri, Sankhya Singh, Shangeetha Sivasothy

CoRR, 2024

Quantifying Manifolds: Do the manifolds learned by Generative Adversarial Networks converge to the real data manifold.

Anupam Chaudhuri, Anj Simmons, Mohamed Abdelrazek

CoRR, 2024

Green Runner: A Tool for Efficient Deep Learning Component Selection.

Jai Kannan, Scott Barnett, Anj Simmons, Taylan Selvi, Luis Cruz

Proceedings of the IEEE/ACM 3rd International Conference on AI Engineering, 2024

2023

Estimating Patient-Level Uncertainty in Seizure Detection Using Group-Specific Out-of-Distribution Detection Technique.

Sheng Wong, Anj Simmons, Jessica Rivera-Villicana, Scott Barnett

Sensors, October, 2023

Detecting out-of-distribution text using topological features of transformer-based language models.

Andres Pollano, Anupam Chaudhuri, Anj Simmons

CoRR, 2023

Garbage in, garbage out: Zero-shot detection of crime using Large Language Models.

Anj Simmons, Rajesh Vasa

CoRR, 2023

Green Runner: A tool for efficient model selection from model repositories.

Jai Kannan, Scott Barnett, Anj Simmons, Taylan Selvi, Luis Cruz

CoRR, 2023

MLGuard: Defend Your Machine Learning Model!

Sheng Wong, Scott Barnett, Jessica Rivera-Villicana, Anj Simmons, Hala Abdelkader, Jean-Guy Schneider, Rajesh Vasa

Proceedings of the 1st International Workshop on Dependability and Trustworthiness of Safety-Critical Systems with Machine Learned Components, 2023

2022

Comparative analysis of real bugs in open-source Machine Learning projects - A Registered Report.

Tuan Dung Lai, Anj Simmons, Scott Barnett, Jean-Guy Schneider, Rajesh Vasa

CoRR, 2022

Signal Knowledge Graph.

Anj Simmons, Rajesh Vasa

CoRR, 2022

A reliability measure for smart surveillance systems.

Anj Simmons

CoRR, 2022

SignalKG: Towards Reasoning about the Underlying Causes of Sensor Observations.

Anj Simmons, Rajesh Vasa, Antonio Giardina

Proceedings of the ISWC 2022 Posters, 2022

MLSmellHound: A Context-Aware Code Analysis Tool.

Jai Kannan, Scott Barnett, Luis Cruz, Anj Simmons, Akash Agarwal

Proceedings of the 44th IEEE/ACM International Conference on Software Engineering: New Ideas and Emerging Results ICSE (NIER) 2022, 2022

2021

Towards a taxonomy for annotation of data science experiment repositories.

Shangeetha Sivasothy, Scott Barnett, Niroshinie Fernando, Rajesh Vasa, Roopak Sinha, Andrew J. Simmons

Proceedings of the 21st IEEE International Working Conference on Source Code Analysis and Manipulation, 2021

2020

An end-to-end model-based approach to support big data analytics development.

Hourieh Khalajzadeh, Andrew J. Simmons, Mohamed Abdelrazek, John C. Grundy, John G. Hosking, Qiang He

J. Comput. Lang., 2020

End-User-Oriented Tool Support for Modeling Data Analytics Requirements.

Hourieh Khalajzadeh, Andrew J. Simmons, Mohamed Abdelrazek, John Grundy, John G. Hosking, Qiang He

Proceedings of the IEEE Symposium on Visual Languages and Human-Centric Computing, 2020

User-centred tooling for modelling of big data applications.

Hourieh Khalajzadeh, Tarun Verma, Andrew J. Simmons, John C. Grundy, Mohamed Abdelrazek, John G. Hosking

Proceedings of the MODELS '20: ACM/IEEE 23rd International Conference on Model Driven Engineering Languages and Systems, 2020

A practical, collaborative approach for modeling big data analytics application requirements.

Hourieh Khalajzadeh, Andrew J. Simmons, Mohamed Abdelrazek, John C. Grundy, John G. Hosking, Qiang He, Prasanna Ratnakanthan, Adil Zia, Meng Law

Proceedings of the ICSE '20: 42nd International Conference on Software Engineering, Companion Volume, Seoul, South Korea, 27 June, 2020

A large-scale comparative analysis of Coding Standard conformance in Open-Source Data Science projects.

Andrew J. Simmons, Scott Barnett, Jessica Rivera-Villicana, Akshat Bajaj, Rajesh Vasa

Proceedings of the ESEM '20: ACM / IEEE International Symposium on Empirical Software Engineering and Measurement, 2020

BiDaML in Practice: Collaborative Modeling of Big Data Analytics Application Requirements.

Hourieh Khalajzadeh, Andrew J. Simmons, Tarun Verma, Mohamed Abdelrazek, John C. Grundy, John G. Hosking, Qiang He, Prasanna Ratnakanthan, Adil Zia, Meng Law

Proceedings of the Evaluation of Novel Approaches to Software Engineering, 2020

Visual Languages for Supporting Big Data Analytics Development.

Hourieh Khalajzadeh, Andrew J. Simmons, Mohamed Abdelrazek, John Grundy, John G. Hosking, Qiang He

Proceedings of the 15th International Conference on Evaluation of Novel Approaches to Software Engineering, 2020

2018

Data Provenance for Sport.

Andrew J. Simmons, Scott Barnett, Simon Vajda, Rajesh Vasa

CoRR, 2018

An interaction model for de-identification of human data held by external custodians.

Andrew J. Simmons, Maheswaree Kissoon Curumsing, Rajesh Vasa

Proceedings of the 30th Australian Conference on Computer-Human Interaction, 2018

2017

Spatio-Temporal Reference Frames as Geographic Objects.

Andrew J. Simmons, Rajesh Vasa

Proceedings of the 25th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2017

2016

Agree to disagree: on labelling helpful app reviews.

Andrew J. Simmons, Leonard Hoon

Proceedings of the 28th Australian Conference on Computer-Human Interaction, 2016

2015

Hub Map: A new approach for visualizing traffic data sets with multi-attribute link data.

Andrew J. Simmons, Iman Avazpour, Hai Le Vu, Rajesh Vasa

Proceedings of the 2015 IEEE Symposium on Visual Languages and Human-Centric Computing, 2015