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Richard Tomsett
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2020 – today
- 2022
- [j2]Charvi Rastogi, Yunfeng Zhang, Dennis Wei, Kush R. Varshney, Amit Dhurandhar, Richard Tomsett:
Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making. Proc. ACM Hum. Comput. Interact. 6(CSCW1): 83:1-83:22 (2022) - 2020
- [j1]Richard Tomsett, Alun D. Preece, Dave Braines, Federico Cerutti, Supriyo Chakraborty, Mani B. Srivastava, Gavin Pearson, Lance M. Kaplan:
Rapid Trust Calibration through Interpretable and Uncertainty-Aware AI. Patterns 1(4): 100049 (2020) - [c9]Richard Tomsett, Dan Harborne, Supriyo Chakraborty, Prudhvi Gurram, Alun D. Preece:
Sanity Checks for Saliency Metrics. AAAI 2020: 6021-6029 - [i6]Liam Hiley, Alun D. Preece, Yulia Hicks, Supriyo Chakraborty, Prudhvi Gurram, Richard Tomsett:
Explaining Motion Relevance for Activity Recognition in Video Deep Learning Models. CoRR abs/2003.14285 (2020) - [i5]Charvi Rastogi, Yunfeng Zhang, Dennis Wei, Kush R. Varshney, Amit Dhurandhar, Richard Tomsett:
Deciding Fast and Slow: The Role of Cognitive Biases in AI-assisted Decision-making. CoRR abs/2010.07938 (2020)
2010 – 2019
- 2019
- [c8]Dave Braines, Richard Tomsett, Alun D. Preece:
Supporting User Fusion of AI Services through Conversational Explanations. FUSION 2019: 1-8 - [c7]Chris Simpkin, Ian J. Taylor, Alun D. Preece, Graham A. Bent, Richard Tomsett, Raghu K. Ganti, Olwen Worthington:
Coalition C3 Information Exchange Using Binary Symbolic Vectors. MILCOM 2019: 784-789 - [c6]Deboleena Roy, Gopalakrishnan Srinivasan, Priyadarshini Panda, Richard Tomsett, Nirmit Desai, Raghu K. Ganti, Kaushik Roy:
Neural Networks at the Edge. SMARTCOMP 2019: 45-50 - [c5]Richard Tomsett, Graham A. Bent, Christopher Simpkin, Ian J. Taylor, Daniel Harborne, Alun D. Preece, Raghu K. Ganti:
Demonstration of Dynamic Distributed Orchestration of Node-RED IoT Workflows Using a Vector Symbolic Architecture. SMARTCOMP 2019: 464-467 - [i4]David Mott, Richard Tomsett:
Illuminated Decision Trees with Lucid. CoRR abs/1909.05644 (2019) - [i3]Richard Tomsett, Dan Harborne, Supriyo Chakraborty, Prudhvi Gurram, Alun D. Preece:
Sanity Checks for Saliency Metrics. CoRR abs/1912.01451 (2019) - 2018
- [c4]Richard Tomsett, Amy Widdicombe, Tianwei Xing, Supriyo Chakraborty, Simon Julier, Prudhvi Gurram, Raghuveer M. Rao, Mani B. Srivastava:
Why the Failure? How Adversarial Examples Can Provide Insights for Interpretable Machine Learning. FUSION 2018: 838-845 - [c3]Alun D. Preece, Dan Harborne, Ramya Raghavendra, Richard Tomsett, Dave Braines:
Provisioning Robust and Interpretable AI/ML-Based Service Bundles. MILCOM 2018: 1-9 - [i2]Richard Tomsett, Dave Braines, Dan Harborne, Alun D. Preece, Supriyo Chakraborty:
Interpretable to Whom? A Role-based Model for Analyzing Interpretable Machine Learning Systems. CoRR abs/1806.07552 (2018) - [i1]Alun D. Preece, Dan Harborne, Dave Braines, Richard Tomsett, Supriyo Chakraborty:
Stakeholders in Explainable AI. CoRR abs/1810.00184 (2018) - 2017
- [c2]Supriyo Chakraborty, Richard Tomsett, Ramya Raghavendra, Daniel Harborne, Moustafa Alzantot, Federico Cerutti, Mani B. Srivastava, Alun D. Preece, Simon Julier, Raghuveer M. Rao, Troy D. Kelley, Dave Braines, Murat Sensoy, Christopher J. Willis, Prudhvi Gurram:
Interpretability of deep learning models: A survey of results. SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017: 1-6 - [c1]Alistair Nottle, Daniel Harborne, Dave Braines, Moustafa Alzantot, Santiago Quintana-Amate, Richard Tomsett, Lance M. Kaplan, Mani B. Srivastava, Supriyo Chakraborty, Alun D. Preece:
Distributed opportunistic sensing and fusion for traffic congestion detection. SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI 2017: 1-6
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