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2020 – today
- 2024
[j9]William Leeney
, Ryan McConville:
Uncertainty in GNN Learning Evaluations: A Comparison between Measures for Quantifying Randomness in GNN Community Detection. Entropy 26(1): 78 (2024)- [i24]William Leeney, Ryan McConville:
Unsupervised Optimisation of GNNs for Node Clustering. CoRR abs/2402.07845 (2024) - 2023
- [j8]Dominika Nadia Wojtczak, Claudia Peersman, Luisa Zuccolo, Ryan McConville:
Characterizing Discourse and Engagement Across Topics of Misinformation on Twitter. IEEE Access 11: 115002-115010 (2023) - [j7]Harry Emerson, Matthew Guy, Ryan McConville:
Offline reinforcement learning for safer blood glucose control in people with type 1 diabetes. J. Biomed. Informatics 142: 104376 (2023) - [c31]William Leeney, Ryan McConville:
Uncertainty in GNN Learning Evaluations: The Importance of a Consistent Benchmark for Community Detection. COMPLEX NETWORKS (1) 2023: 112-123 - [c30]Yiwen Wu, Kevin McAreavey, Weiru Liu, Ryan McConville:
A Comparative Analysis of Information Cascade Prediction Using Dynamic Heterogeneous and Homogeneous Graphs. COMPLEX NETWORKS (4) 2023: 168-179 - [c29]Andrés Domínguez Hernández, Richard Owen, Dan Saattrup Nielsen, Ryan McConville:
Addressing contingency in algorithmic (mis)information classification: Toward a responsible machine learning agenda. FAccT 2023: 971 - [c28]Ferdian Jovan, Catherine Morgan, Ryan McConville, Emma L. Tonkin, Ian Craddock, Alan L. Whone:
Multimodal Indoor Localisation in Parkinson's Disease for Detecting Medication Use: Observational Pilot Study in a Free-Living Setting. KDD 2023: 4273-4283 - [c27]Hongbo Bo, Yiwen Wu, Zinuo You, Ryan McConville, Jun Hong, Weiru Liu:
What Will Make Misinformation Spread: An XAI Perspective. xAI (2) 2023: 321-337 - [i23]Will Leeney, Ryan McConville:
Search for the UGLE Truth: An Investigation into Unsupervised GNN Learning Environments. CoRR abs/2305.06026 (2023) - [i22]Alex Iacob, Pedro Porto Buarque de Gusmão, Nicholas D. Lane, Armand K. Koupai, Mohammud Junaid Bocus, Raúl Santos-Rodríguez, Robert J. Piechocki, Ryan McConville:
Privacy in Multimodal Federated Human Activity Recognition. CoRR abs/2305.12134 (2023) - [i21]Ferdian Jovan, Catherine Morgan, Ryan McConville, Emma L. Tonkin, Ian Craddock, Alan L. Whone:
Multimodal Indoor Localisation in Parkinson's Disease for Detecting Medication Use: Observational Pilot Study in a Free-Living Setting. CoRR abs/2308.02419 (2023) - [i20]Harry Emerson, Ryan McConville, Matthew Guy:
The Safety Challenges of Deep Learning in Real-World Type 1 Diabetes Management. CoRR abs/2310.14743 (2023) - [i19]William Leeney, Ryan McConville:
Uncertainty in GNN Learning Evaluations: A Comparison Between Measures for Quantifying Randomness in GNN Community Detection. CoRR abs/2312.09015 (2023) - [i18]William Leeney, Ryan McConville:
A Framework for Exploring Federated Community Detection. CoRR abs/2312.09023 (2023) - 2022
- [j6]Armand K. Koupai, Mohammud Junaid Bocus, Raúl Santos-Rodríguez, Robert J. Piechocki, Ryan McConville:
Self-supervised multimodal fusion transformer for passive activity recognition. IET Wirel. Sens. Syst. 12(5-6): 149-160 (2022) - [j5]Ki-Young Shin, Ryan McConville, Oussama Metatla, Min Hye Chang, Chiyoung Han, Junhaeng Lee, Anne Roudaut:
Outdoor Localization Using BLE RSSI and Accessible Pedestrian Signals for the Visually Impaired at Intersections. Sensors 22(1): 371 (2022) - [c26]Roisin McNaney, Catherine Morgan, Pranav Kulkarni, Julio Vega, Farnoosh Heidarivincheh, Ryan McConville, Alan L. Whone, Mickey Kim, Reuben Kirkham, Ian Craddock:
Exploring Perceptions of Cross-Sectoral Data Sharing with People with Parkinson's. CHI 2022: 280:1-280:14 - [c25]Francesco Raimondo, Ufuk Erol, Samuel Gunner, James Pope, Robert Zakrzewski, Mike Faulks, Ryan McConville, Thomas Pasquier, Robert J. Piechocki, George Oikonomou:
IoT Key Exchange Performance Analysis. EWSN 2022: 238-243 - [c24]Mohammud Junaid Bocus, Hok-Shing Lau, Ryan McConville, Robert J. Piechocki, Raúl Santos-Rodríguez:
Self-Supervised WiFi-Based Activity Recognition. GLOBECOM (Workshops) 2022: 552-557 - [c23]Jonas Paulavicius, Seifallah Jardak, Ryan McConville, Robert J. Piechocki, Raúl Santos-Rodríguez:
Temporal Self-Supervised Learning for RSSI-based Indoor Localization. ICC 2022: 3046-3051 - [c22]Hongnan Ma, Kevin McAreavey, Ryan McConville, Weiru Liu:
Explainable AI for Non-Experts: Energy Tariff Forecasting. ICAC 2022: 1-6 - [c21]Hongbo Bo, Ryan McConville, Jun Hong, Weiru Liu:
Ego-graph Replay based Continual Learning for Misinformation Engagement Prediction. IJCNN 2022: 1-8 - [c20]Thanaphon Suwannaphong, Ryan McConville, Ian Craddock:
Radio signal strength indication augmentation for one-shot learning in indoor localisation. SmartWear@MobiCom 2022: 7-12 - [c19]Dan Saattrup Nielsen, Ryan McConville:
MuMiN: A Large-Scale Multilingual Multimodal Fact-Checked Misinformation Social Network Dataset. SIGIR 2022: 3141-3153 - [i17]Dan Saattrup Nielsen, Ryan McConville:
MuMiN: A Large-Scale Multilingual Multimodal Fact-Checked Misinformation Social Network Dataset. CoRR abs/2202.11684 (2022) - [i16]Harry Emerson, Matthew Guy, Ryan McConville:
Offline Reinforcement Learning for Safer Blood Glucose Control in People with Type 1 Diabetes. CoRR abs/2204.03376 (2022) - [i15]Ferdian Jovan, Ryan McConville, Catherine Morgan, Emma Tonkin, Alan L. Whone, Ian Craddock:
Multimodal Indoor Localisation for Measuring Mobility in Parkinson's Disease using Transformers. CoRR abs/2205.06142 (2022) - [i14]Hongbo Bo, Ryan McConville, Jun Hong, Weiru Liu:
Ego-graph Replay based Continual Learning for Misinformation Engagement Prediction. CoRR abs/2207.12105 (2022) - [i13]Armand K. Koupai, Mohammud Junaid Bocus, Raúl Santos-Rodríguez, Robert J. Piechocki, Ryan McConville:
Self-Supervised Multimodal Fusion Transformer for Passive Activity Recognition. CoRR abs/2209.03765 (2022) - [i12]Andrés Domínguez Hernández, Richard Owen, Dan Saattrup Nielsen, Ryan McConville:
Addressing contingency in algorithmic misinformation detection: Toward a responsible innovation agenda. CoRR abs/2210.09014 (2022) - [i11]James Pope, Jinyuan Liang, Vijay Kumar, Francesco Raimondo, Xinyi Sun, Ryan McConville, Thomas Pasquier, Robert J. Piechocki, George Oikonomou, Bo Luo, Dan Howarth, Ioannis Mavromatis, Adrián Sánchez-Mompó, Pietro Edoardo Carnelli, Theodoros Spyridopoulos, Aftab Khan:
Resource-Interaction Graph: Efficient Graph Representation for Anomaly Detection. CoRR abs/2212.08525 (2022) - 2021
- [j4]Ryan McConville, Gareth Archer, Ian Craddock, Michal Kozlowski, Robert J. Piechocki, James Pope, Raúl Santos-Rodríguez:
Vesta: A digital health analytics platform for a smart home in a box. Future Gener. Comput. Syst. 114: 106-119 (2021) - [j3]Farnoosh Heidarivincheh, Ryan McConville, Catherine Morgan, Roisin McNaney, Alessandro Masullo, Majid Mirmehdi, Alan L. Whone, Ian Craddock:
Multimodal Classification of Parkinson's Disease in Home Environments with Resiliency to Missing Modalities. Sensors 21(12): 4133 (2021) - [c18]Hongbo Bo, Ryan McConville, Jun Hong, Weiru Liu:
Social Influence Prediction with Train and Test Time Augmentation for Graph Neural Networks. IJCNN 2021: 1-8 - [c17]Catherine Morgan, Farnoosh Heidarivincheh, Ian Craddock, Ryan McConville, Miquel Perelló-Nieto, Emma L. Tonkin, Alessandro Masullo, Antonis Vafeas, Mickey Kim, Roisin McNaney, Gregory J. L. Tourte, Alan L. Whone:
Data labelling in the wild: annotating free-living activities and Parkinson's disease symptoms. PerCom Workshops 2021: 471-474 - [c16]James Pope, Francesco Raimondo, Vijay Kumar, Ryan McConville, Robert J. Piechocki, George Oikonomou, Thomas Pasquier, Bo Luo, Dan Howarth, Ioannis Mavromatis, Pietro Edoardo Carnelli, Adrián Sánchez-Mompó, Theodoros Spyridopoulos, Aftab Khan:
Container Escape Detection for Edge Devices. SenSys 2021: 532-536 - [i10]Hok-Shing Lau, Ryan McConville, Mohammud Junaid Bocus, Robert J. Piechocki, Raúl Santos-Rodríguez:
Self-Supervised WiFi-Based Activity Recognition. CoRR abs/2104.09072 (2021) - [i9]Hongbo Bo, Ryan McConville, Jun Hong, Weiru Liu:
Social Influence Prediction with Train and Test Time Augmentation for Graph Neural Networks. CoRR abs/2104.11641 (2021) - [i8]James Neve, Ryan McConville:
Photos Are All You Need for Reciprocal Recommendation in Online Dating. CoRR abs/2108.11714 (2021) - [i7]Taku Yamagata, Ryan McConville, Raúl Santos-Rodríguez:
Reinforcement Learning with Feedback from Multiple Humans with Diverse Skills. CoRR abs/2111.08596 (2021) - 2020
- [j2]Atis Elsts, Niall Twomey, Ryan McConville, Ian Craddock:
Energy-efficient activity recognition framework using wearable accelerometers. J. Netw. Comput. Appl. 168: 102770 (2020) - [c15]Mohammud Junaid Bocus, Jonas Paulavicius, Ryan McConville, Raúl Santos-Rodríguez, Robert J. Piechocki:
Low Cost Localisation in Residential Environments using High Resolution CIR Information. GLOBECOM 2020: 1-6 - [c14]Alexander Hepburn, Valero Laparra, Jesús Malo, Ryan McConville, Raúl Santos-Rodríguez:
Perceptnet: A Human Visual System Inspired Neural Network For Estimating Perceptual Distance. ICIP 2020: 121-125 - [c13]Ryan McConville, Raúl Santos-Rodríguez, Robert J. Piechocki, Ian Craddock:
N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded Embedding. ICPR 2020: 5145-5152 - [c12]Mohammud Junaid Bocus, Wenda Li, Jonas Paulavicius, Ryan McConville, Raúl Santos-Rodríguez, Kevin Chetty, Robert J. Piechocki:
Translation Resilient Opportunistic WiFi Sensing. ICPR 2020: 5627-5633 - [c11]Alexander Hepburn, Valero Laparra, Ryan McConville, Raúl Santos-Rodríguez:
Enforcing perceptual consistency on Generative Adversarial Networks by using the Normalised Laplacian Pyramid Distance. NLDL 2020: 1-6 - [c10]James Neve, Ryan McConville:
ImRec: Learning Reciprocal Preferences Using Images. RecSys 2020: 170-179 - [c9]Hongbo Bo, Ryan McConville, Jun Hong, Weiru Liu:
Social Network Influence Ranking via Embedding Network Interactions for User Recommendation. WWW (Companion Volume) 2020: 379-384
2010 – 2019
- 2019
- [i6]Alexander Hepburn, Valero Laparra, Ryan McConville, Raúl Santos-Rodríguez:
Enforcing Perceptual Consistency on Generative Adversarial Networks by Using the Normalised Laplacian Pyramid Distance. CoRR abs/1908.04347 (2019) - [i5]Ryan McConville, Raúl Santos-Rodríguez, Robert J. Piechocki, Ian Craddock:
N2D: (Not Too) Deep Clustering via Clustering the Local Manifold of an Autoencoded Embedding. CoRR abs/1908.05968 (2019) - [i4]Taku Yamagata, Raúl Santos-Rodríguez, Ryan McConville, Atis Elsts:
Online Feature Selection for Activity Recognition using Reinforcement Learning with Multiple Feedback. CoRR abs/1908.06134 (2019) - [i3]Alexander Hepburn, Valero Laparra, Jesús Malo, Ryan McConville, Raúl Santos-Rodríguez:
PerceptNet: A Human Visual System Inspired Neural Network for Estimating Perceptual Distance. CoRR abs/1910.12548 (2019) - 2018
- [j1]Niall Twomey, Tom Diethe, Xenofon Fafoutis, Atis Elsts, Ryan McConville, Peter A. Flach, Ian Craddock:
A Comprehensive Study of Activity Recognition Using Accelerometers. Informatics 5(2): 27 (2018) - [c8]Ryan McConville, Raúl Santos-Rodríguez, Niall Twomey:
Person Identification and Discovery With Wrist Worn Accelerometer Data. ESANN 2018 - [c7]Atis Elsts, Ryan McConville, Xenofon Fafoutis, Niall Twomey, Robert J. Piechocki, Raúl Santos-Rodriguez, Ian Craddock:
On-Board Feature Extraction from Acceleration Data for Activity Recognition. EWSN 2018: 163-168 - [c6]Alexander Hepburn, Ryan McConville, Raúl Santos-Rodríguez, Jesús Cid-Sueiro, Dario García-García:
Proper Losses for Learning with Example-Dependent Costs. LIDTA@ECML/PKDD 2018: 52-66 - [c5]Ryan McConville, Dallan Byrne, Ian Craddock, Robert J. Piechocki, James Pope, Raúl Santos-Rodríguez:
Understanding the quality of calibrations for indoor localisation. WF-IoT 2018: 676-681 - [i2]Ryan McConville, Gareth Archer, Ian Craddock, Herman J. ter Horst, Robert J. Piechocki, James Pope, Raúl Santos-Rodriguez:
Online Heart Rate Prediction using Acceleration from a Wrist Worn Wearable. CoRR abs/1807.04667 (2018) - [i1]Michal Kozlowski, Ryan McConville, Raúl Santos-Rodríguez, Robert J. Piechocki:
Energy Efficiency in Reinforcement Learning for Wireless Sensor Networks. CoRR abs/1812.02538 (2018) - 2017
- [b1]Ryan McConville:
Clustering algorithms for large scale graph data. Queen's University Belfast, UK, 2017 - [c4]Ryan McConville, Weiru Liu, Jun Hong:
Vertex Deduplication Based on String Similarity and Community Membership. COMPLEX NETWORKS 2017: 178-189 - [c3]James Pope, Ryan McConville, Michal Kozlowski, Xenofon Fafoutis, Raúl Santos-Rodríguez, Robert J. Piechocki, Ian Craddock:
SPHERE in a Box: Practical and Scalable EurValve Activity Monitoring Smart Home Kit. LCN Workshops 2017: 128-135 - 2016
- [c2]Ryan McConville, Xin Cao, Weiru Liu, Paul Miller:
Accelerating large scale centroid-based clustering with locality sensitive hashing. ICDE 2016: 649-660 - 2015
- [c1]Ryan McConville, Weiru Liu, Paul Miller:
Vertex Clustering of Augmented Graph Streams. SDM 2015: 109-117
Coauthor Index
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last updated on 2024-10-07 21:23 CEST by the dblp team
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