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Mark Coates
Mark J. Coates – M. J. Coates
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- affiliation: McGill University, Montreal, Canada
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2020 – today
- 2024
- [j44]Soumyasundar Pal
, Antonios Valkanas
, Mark Coates
:
Population Monte Carlo With Normalizing Flow. IEEE Signal Process. Lett. 31: 16-20 (2024) - [j43]Mohammad Ali Alomrani, Mahdi Biparva, Yingxue Zhang, Mark Coates:
DyG2Vec: Efficient Representation Learning for Dynamic Graphs. Trans. Mach. Learn. Res. 2024 (2024) - [j42]Boris N. Oreshkin
, Antonios Valkanas
, Félix G. Harvey, Louis-Simon Ménard, Florent Bocquelet, Mark J. Coates
:
Motion In-Betweening via Deep $\Delta$Δ-Interpolator. IEEE Trans. Vis. Comput. Graph. 30(8): 5693-5704 (2024) - [c120]Florence Regol, Mark Coates:
Categorical Generative Model Evaluation via Synthetic Distribution Coarsening. AISTATS 2024: 910-918 - [c119]Yitian Zhang, Liheng Ma, Soumyasundar Pal, Yingxue Zhang, Mark Coates:
Multi-resolution Time-Series Transformer for Long-term Forecasting. AISTATS 2024: 4222-4230 - [c118]Yuening Wang
, Man Chen
, Yaochen Hu
, Wei Guo
, Yingxue Zhang
, Huifeng Guo
, Yong Liu
, Mark Coates
:
Enhancing Click-through Rate Prediction in Recommendation Domain with Search Query Representation. CIKM 2024: 2462-2471 - [c117]Florence Regol, Joud Chataoui, Mark Coates:
Jointly-Learned Exit and Inference for a Dynamic Neural Network. ICLR 2024 - [c116]Liheng Ma, Soumyasundar Pal, Yitian Zhang, Jiaming Zhou, Yingxue Zhang, Mark Coates:
CKGConv: General Graph Convolution with Continuous Kernels. ICML 2024 - [c115]Mai Zeng, Florence Regol, Mark Coates:
Interacting Diffusion Processes for Event Sequence Forecasting. ICML 2024 - [c114]Zhanguang Zhang
, Didier Chételat
, Joseph Cotnareanu
, Amur Ghose
, Wenyi Xiao
, Hui-Ling Zhen
, Yingxue Zhang
, Jianye Hao
, Mark Coates
, Mingxuan Yuan
:
GraSS: Combining Graph Neural Networks with Expert Knowledge for SAT Solver Selection. KDD 2024: 6301-6311 - [c113]Joseph Cotnareanu, Zhanguang Zhang, Hui-Ling Zhen, Yingxue Zhang, Mark Coates:
HardCore Generation: Generating Hard UNSAT Problems for Data Augmentation. NeurIPS 2024 - [i64]Antonios Valkanas, Yuening Wang, Yingxue Zhang, Mark Coates:
Personalized Negative Reservoir for Incremental Learning in Recommender Systems. CoRR abs/2403.03993 (2024) - [i63]Liheng Ma, Soumyasundar Pal, Yitian Zhang, Jiaming Zhou, Yingxue Zhang, Mark Coates:
CKGConv: General Graph Convolution with Continuous Kernels. CoRR abs/2404.13604 (2024) - [i62]Zhanguang Zhang, Didier Chételat, Joseph Cotnareanu, Amur Ghose, Wenyi Xiao, Hui-Ling Zhen, Yingxue Zhang, Jianye Hao, Mark Coates, Mingxuan Yuan:
GraSS: Combining Graph Neural Networks with Expert Knowledge for SAT Solver Selection. CoRR abs/2405.11024 (2024) - [i61]Antonios Valkanas, Boris N. Oreshkin, Mark Coates:
MODL: Multilearner Online Deep Learning. CoRR abs/2405.18281 (2024) - [i60]Pavel Rumiantsev, Mark Coates:
Graph Knowledge Distillation to Mixture of Experts. CoRR abs/2406.11919 (2024) - [i59]Florence Regol, Joud Chataoui, Bertrand Charpentier, Mark Coates, Pablo Piantanida, Stephan Günnemann:
Predicting Probabilities of Error to Combine Quantization and Early Exiting: QuEE. CoRR abs/2406.14404 (2024) - [i58]Jiaming Zhou, Abbas Ghaddar, Ge Zhang, Liheng Ma, Yaochen Hu, Soumyasundar Pal, Mark Coates, Bin Wang, Yingxue Zhang, Jianye Hao:
Enhancing Logical Reasoning in Large Language Models through Graph-based Synthetic Data. CoRR abs/2409.12437 (2024) - [i57]Joseph Cotnareanu, Zhanguang Zhang, Hui-Ling Zhen, Yingxue Zhang, Mark Coates:
HardCore Generation: Generating Hard UNSAT Problems for Data Augmentation. CoRR abs/2409.18778 (2024) - [i56]Yaochen Hu, Mai Zeng, Ge Zhang, Pavel Rumiantsev, Liheng Ma, Yingxue Zhang, Mark Coates:
Sparse Decomposition of Graph Neural Networks. CoRR abs/2410.19723 (2024) - [i55]Theodore Glavas, Joud Chataoui, Florence Regol, Wassim Jabbour, Antonios Valkanas, Boris N. Oreshkin, Mark Coates:
Dynamic layer selection in decoder-only transformers. CoRR abs/2410.20022 (2024) - [i54]Yuening Wang, Chen Ma, Yaochen Hu, Wei Guo, Yingxue Zhang, Huifeng Guo, Yong Liu, Mark Coates:
Enhancing CTR Prediction in Recommendation Domain with Search Query Representation. CoRR abs/2410.21487 (2024) - [i53]Julien Nicolas, César Sabater, Mohamed Maouche, Sonia Ben Mokhtar, Mark Coates:
Differentially private and decentralized randomized power method. CoRR abs/2411.01931 (2024) - [i52]Soumyasundar Pal, Didier Chételat, Yingxue Zhang, Mark Coates:
Hint Marginalization for Improved Reasoning in Large Language Models. CoRR abs/2412.13292 (2024) - [i51]Ge Zhang, Mohammad Ali Alomrani, Hongjian Gu, Jiaming Zhou, Yaochen Hu, Bin Wang, Qun Liu, Mark Coates, Yingxue Zhang, Jianye Hao:
Path-of-Thoughts: Extracting and Following Paths for Robust Relational Reasoning with Large Language Models. CoRR abs/2412.17963 (2024) - 2023
- [c112]Yuening Wang, Yingxue Zhang, Antonios Valkanas, Ruiming Tang, Chen Ma
, Jianye Hao, Mark Coates:
Structure Aware Incremental Learning with Personalized Imitation Weights for Recommender Systems. AAAI 2023: 4711-4719 - [c111]Florence Regol, Mark Coates:
Diffusing Gaussian Mixtures for Generating Categorical Data. AAAI 2023: 9570-9578 - [c110]Mehrtash Mehrabi, Walid Masoudimansour, Yingxue Zhang, Jie Chuai, Zhitang Chen, Mark Coates, Jianye Hao, Yanhui Geng:
Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network. AAAI 2023: 14400-14407 - [c109]Amur Ghose, Yingxue Zhang, Jianye Hao, Mark Coates:
Spectral Augmentations for Graph Contrastive Learning. AISTATS 2023: 11213-11266 - [c108]Muberra Ozmen, Joseph Cotnareanu, Mark Coates:
Substituting Data Annotation with Balanced Neighbourhoods and Collective Loss in Multi-label Text Classification. CoLLAs 2023: 909-922 - [c107]Florence Regol, Anja Kroon, Mark Coates:
Evaluation of Categorical Generative Models - Bridging the Gap Between Real and Synthetic Data. ICASSP 2023: 1-5 - [c106]Pavel Rumiantsev, Mark Coates:
Performing Neural Architecture Search Without Gradients. ICASSP 2023: 1-5 - [c105]Haolun Wu, Yingxue Zhang, Chen Ma
, Wei Guo, Ruiming Tang
, Xue Liu, Mark Coates:
Intent-aware Multi-source Contrastive Alignment for Tag-enhanced Recommendation. ICDE 2023: 1112-1125 - [c104]Can Chen, Yingxue Zhang, Xue Liu, Mark Coates:
Bidirectional Learning for Offline Model-based Biological Sequence Design. ICML 2023: 5351-5366 - [c103]Liheng Ma, Chen Lin, Derek Lim, Adriana Romero-Soriano, Puneet K. Dokania, Mark Coates, Philip H. S. Torr, Ser-Nam Lim:
Graph Inductive Biases in Transformers without Message Passing. ICML 2023: 23321-23337 - [c102]Kiarash Zahirnia, Yaochen Hu, Mark Coates, Oliver Schulte:
Neural Graph Generation from Graph Statistics. NeurIPS 2023 - [e1]Marina L. Gavrilova
, C. J. Kenneth Tan, Mark Coates, Yaoping Hu, Henry Leung, Arash Mohammadi, Konstantinos N. Plataniotis, Helder Rodrigues de Oliveira:
Transactions on Computational Science XL. Lecture Notes in Computer Science 13850, Springer 2023, ISBN 978-3-662-67867-1 [contents] - [i50]Can Chen, Yingxue Zhang, Xue Liu, Mark Coates:
Bidirectional Learning for Offline Model-based Biological Sequence Design. CoRR abs/2301.02931 (2023) - [i49]Mehrtash Mehrabi, Walid Masoudimansour, Yingxue Zhang, Jie Chuai, Zhitang Chen, Mark Coates, Jianye Hao, Yanhui Geng:
Neighbor Auto-Grouping Graph Neural Networks for Handover Parameter Configuration in Cellular Network. CoRR abs/2301.03412 (2023) - [i48]Amur Ghose, Yingxue Zhang, Jianye Hao, Mark Coates:
Spectral Augmentations for Graph Contrastive Learning. CoRR abs/2302.02909 (2023) - [i47]Florence Regol, Mark Coates:
Diffusing Gaussian Mixtures for Generating Categorical Data. CoRR abs/2303.04635 (2023) - [i46]Yuening Wang, Yingxue Zhang, Antonios Valkanas, Ruiming Tang
, Chen Ma, Jianye Hao, Mark Coates:
Structure Aware Incremental Learning with Personalized Imitation Weights for Recommender Systems. CoRR abs/2305.01204 (2023) - [i45]Liheng Ma, Chen Lin, Derek Lim, Adriana Romero-Soriano, Puneet K. Dokania, Mark Coates, Philip H. S. Torr, Ser-Nam Lim:
Graph Inductive Biases in Transformers without Message Passing. CoRR abs/2305.17589 (2023) - [i44]Muberra Ozmen, Joseph Cotnareanu, Mark Coates:
Substituting Data Annotation with Balanced Updates and Collective Loss in Multi-label Text Classification. CoRR abs/2309.13543 (2023) - [i43]Florence Regol, Joud Chataoui, Mark Coates:
Jointly-Learned Exit and Inference for a Dynamic Neural Network : JEI-DNN. CoRR abs/2310.09163 (2023) - [i42]Mai Zeng, Florence Regol, Mark Coates:
Interacting Diffusion Processes for Event Sequence Forecasting. CoRR abs/2310.17800 (2023) - [i41]Yitian Zhang, Liheng Ma, Soumyasundar Pal, Yingxue Zhang, Mark Coates:
Multi-resolution Time-Series Transformer for Long-term Forecasting. CoRR abs/2311.04147 (2023) - 2022
- [j41]Florence Regol, Soumyasundar Pal, Jianing Sun, Yingxue Zhang, Yanhui Geng, Mark Coates:
Node copying: A random graph model for effective graph sampling. Signal Process. 192: 108335 (2022) - [j40]Yitian Zhang
, Huihui Wu
, Mark Coates
:
On the Design of Channel Coding Autoencoders With Arbitrary Rates for ISI Channels. IEEE Wirel. Commun. Lett. 11(2): 426-430 (2022) - [c101]Soumyasundar Pal, Antonios Valkanas, Florence Regol, Mark Coates:
Bag Graph: Multiple Instance Learning Using Bayesian Graph Neural Networks. AAAI 2022: 7922-7930 - [c100]Antonios Valkanas, André-Walter Panzini, Mark Coates:
Towards Bayesian Learning of the Architecture, Graph and Parameters for Graph Neural Networks. IEEECONF 2022: 852-856 - [c99]Haolun Wu, Chen Ma
, Yingxue Zhang, Xue Liu, Ruiming Tang
, Mark Coates:
Adapting Triplet Importance of Implicit Feedback for Personalized Recommendation. CIKM 2022: 2148-2157 - [c98]Yitian Zhang, Florence Regol, Antonios Valkanas, Mark Coates:
Contrastive Learning for Time Series on Dynamic Graphs. EUSIPCO 2022: 742-746 - [c97]Muberra Ozmen, Hao Zhang, Pengyun Wang, Mark Coates:
Multi-Relation Message Passing for Multi-Label Text Classification. ICASSP 2022: 3583-3587 - [c96]Can Chen, Yingxue Zhang, Jie Fu, Xue (Steve) Liu, Mark Coates:
Bidirectional Learning for Offline Infinite-width Model-based Optimization. NeurIPS 2022 - [i40]Boris N. Oreshkin, Antonios Valkanas, Félix G. Harvey, Louis-Simon Ménard, Florent Bocquelet, Mark J. Coates:
Motion Inbetweening via Deep Δ-Interpolator. CoRR abs/2201.06701 (2022) - [i39]Segolene Brivet, Faicel Chamroukhi, Mark Coates, Reza Forghani, Peter Savadjiev:
Spectral image clustering on dual-energy CT scans using functional regression mixtures. CoRR abs/2201.13398 (2022) - [i38]Muberra Ozmen, Hao Zhang, Pengyun Wang, Mark Coates:
Multi-relation Message Passing for Multi-label Text Classification. CoRR abs/2202.04844 (2022) - [i37]Soumyasundar Pal, Antonios Valkanas, Florence Regol, Mark Coates:
Bag Graph: Multiple Instance Learning using Bayesian Graph Neural Networks. CoRR abs/2202.11132 (2022) - [i36]Haolun Wu, Chen Ma, Yingxue Zhang, Xue Liu, Ruiming Tang
, Mark Coates:
Adapting Triplet Importance of Implicit Feedback for Personalized Recommendation. CoRR abs/2208.01709 (2022) - [i35]Florence Regol, Soumyasundar Pal, Jianing Sun, Yingxue Zhang, Yanhui Geng, Mark Coates:
Node Copying: A Random Graph Model for Effective Graph Sampling. CoRR abs/2208.02435 (2022) - [i34]Can Chen, Yingxue Zhang, Jie Fu, Xue Liu, Mark Coates:
Bidirectional Learning for Offline Infinite-width Model-based Optimization. CoRR abs/2209.07507 (2022) - [i33]Yitian Zhang, Florence Regol, Antonios Valkanas, Mark Coates:
Contrastive Learning for Time Series on Dynamic Graphs. CoRR abs/2209.10662 (2022) - [i32]Florence Regol, Anja Kroon, Mark J. Coates:
Evaluation of Categorical Generative Models - Bridging the Gap Between Real and Synthetic Data. CoRR abs/2210.16405 (2022) - [i31]Mohammad Ali Alomrani, Mahdi Biparva, Yingxue Zhang, Mark Coates:
DyG2Vec: Representation Learning for Dynamic Graphs with Self-Supervision. CoRR abs/2210.16906 (2022) - [i30]Haolun Wu, Yingxue Zhang, Chen Ma, Wei Guo, Ruiming Tang
, Xue Liu, Mark Coates:
Intent-aware Multi-source Contrastive Alignment for Tag-enhanced Recommendation. CoRR abs/2211.06370 (2022) - 2021
- [j39]Cody Mazza-Anthony
, Bogdan Mazoure, Mark Coates
:
Learning Gaussian Graphical Models With Ordered Weighted $\ell _1$ Regularization. IEEE Trans. Signal Process. 69: 489-499 (2021) - [c95]Chen Ma
, Liheng Ma, Yingxue Zhang, Haolun Wu, Xue Liu, Mark Coates:
Knowledge-Enhanced Top-K Recommendation in Poincaré Ball. AAAI 2021: 4285-4293 - [c94]Boris N. Oreshkin, Arezou Amini, Lucy Coyle, Mark Coates:
FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting. AAAI 2021: 9233-9241 - [c93]Yingxue Zhang, Florence Regol, Soumyasundar Pal, Sakif Khan, Liheng Ma, Mark Coates:
Detection and Defense of Topological Adversarial Attacks on Graphs. AISTATS 2021: 2989-2997 - [c92]Kian Ahrabian, Yishi Xu, Yingxue Zhang, Jiapeng Wu, Yuening Wang, Mark Coates:
Structure Aware Experience Replay for Incremental Learning in Graph-based Recommender Systems. CIKM 2021: 2832-2836 - [c91]Yuening Wang, Yingxue Zhang, Mark Coates:
Graph Structure Aware Contrastive Knowledge Distillation for Incremental Learning in Recommender Systems. CIKM 2021: 3518-3522 - [c90]Amur Ghose, Vincent Zhang, Yingxue Zhang, Dong Li, Wulong Liu, Mark Coates:
Generalizable Cross-Graph Embedding for GNN-based Congestion Prediction. ICCAD 2021: 1-9 - [c89]Soumyasundar Pal, Liheng Ma, Yingxue Zhang, Mark Coates:
RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting. ICML 2021: 8336-8348 - [c88]Jiapeng Wu, Yishi Xu, Yingxue Zhang, Chen Ma
, Mark Coates, Jackie Chi Kit Cheung:
TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph Completion. SIGIR 2021: 428-437 - [i29]Chen Ma, Liheng Ma, Yingxue Zhang, Ruiming Tang, Xue Liu, Mark Coates:
Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation. CoRR abs/2101.04849 (2021) - [i28]Chen Ma, Liheng Ma, Yingxue Zhang, Haolun Wu, Xue Liu, Mark Coates:
Knowledge-Enhanced Top-K Recommendation in Poincaré Ball. CoRR abs/2101.04852 (2021) - [i27]Jiapeng Wu, Yishi Xu, Yingxue Zhang, Chen Ma, Mark Coates, Jackie Chi Kit Cheung:
TIE: A Framework for Embedding-based Incremental Temporal Knowledge Graph Completion. CoRR abs/2104.08419 (2021) - [i26]Soumyasundar Pal, Liheng Ma, Yingxue Zhang, Mark Coates:
RNN with Particle Flow for Probabilistic Spatio-temporal Forecasting. CoRR abs/2106.06064 (2021) - [i25]Amur Ghose, Vincent Zhang, Yingxue Zhang, Dong Li, Wulong Liu, Mark Coates:
Generalizable Cross-Graph Embedding for GNN-based Congestion Prediction. CoRR abs/2111.05941 (2021) - 2020
- [c87]Chen Ma
, Liheng Ma, Yingxue Zhang, Jianing Sun, Xue Liu, Mark Coates:
Memory Augmented Graph Neural Networks for Sequential Recommendation. AAAI 2020: 5045-5052 - [c86]Antonios Valkanas, Florence Regol, Mark Coates:
Learning from Networks of Distributions. ACSSC 2020: 574-578 - [c85]Yishi Xu, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang
, Mark Coates:
GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems. CIKM 2020: 2861-2868 - [c84]Huihui Wu, Yitian Zhang, Xueqing Zhao, Ningbo Zhu, Mark Coates:
End-to-end Physical Layer Communication using Bi-directional GRUs for ISI Channels. GLOBECOM (Workshops) 2020: 1-6 - [c83]Florence Regol, Soumyasundar Pal, Yingxue Zhang, Mark Coates:
Active Learning on Attributed Graphs via Graph Cognizant Logistic Regression and Preemptive Query Generation. ICML 2020: 8041-8050 - [c82]Chen Ma
, Liheng Ma, Yingxue Zhang, Ruiming Tang
, Xue Liu, Mark Coates:
Probabilistic Metric Learning with Adaptive Margin for Top-K Recommendation. KDD 2020: 1036-1044 - [c81]Jianing Sun, Wei Guo
, Dengcheng Zhang, Yingxue Zhang, Florence Regol, Yaochen Hu, Huifeng Guo, Ruiming Tang
, Han Yuan, Xiuqiang He, Mark Coates:
A Framework for Recommending Accurate and Diverse Items Using Bayesian Graph Convolutional Neural Networks. KDD 2020: 2030-2039 - [c80]Jianing Sun, Yingxue Zhang, Wei Guo
, Huifeng Guo, Ruiming Tang
, Xiuqiang He, Chen Ma
, Mark Coates:
Neighbor Interaction Aware Graph Convolution Networks for Recommendation. SIGIR 2020: 1289-1298 - [c79]Yingxu Wang
, Svetlana N. Yanushkevich
, Ming Hou
, Konstantinos N. Plataniotis, Mark Coates, Marina L. Gavrilova
, Yaoping Hu, Fakhri Karray, Henry Leung, Arash Mohammadi, Sam Kwong
, Edward W. Tunstel, Ljiljana Trajkovic, Imre J. Rudas, Janusz Kacprzyk:
A Tripartite Theory of Trustworthiness for Autonomous Systems. SMC 2020: 3375-3380 - [c78]Soumyasundar Pal, Saber Malekmohammadi, Florence Regol, Yingxue Zhang, Yishi Xu, Mark Coates:
Non Parametric Graph Learning for Bayesian Graph Neural Networks. UAI 2020: 1318-1327 - [i24]Jianing Sun, Yingxue Zhang, Chen Ma, Mark Coates, Huifeng Guo, Ruiming Tang, Xiuqiang He:
Multi-Graph Convolution Collaborative Filtering. CoRR abs/2001.00267 (2020) - [i23]Soumyasundar Pal, Saber Malekmohammadi, Florence Regol, Yingxue Zhang, Yishi Xu, Mark Coates:
Non-Parametric Graph Learning for Bayesian Graph Neural Networks. CoRR abs/2006.13335 (2020) - [i22]Florence Regol, Soumyasundar Pal, Yingxue Zhang, Mark Coates:
Active Learning on Attributed Graphs via Graph Cognizant Logistic Regression and Preemptive Query Generation. CoRR abs/2007.05003 (2020) - [i21]Florence Regol, Soumyasundar Pal, Mark Coates:
Node Copying for Protection Against Graph Neural Network Topology Attacks. CoRR abs/2007.06704 (2020) - [i20]Boris N. Oreshkin, Arezou Amini, Lucy Coyle, Mark J. Coates:
FC-GAGA: Fully Connected Gated Graph Architecture for Spatio-Temporal Traffic Forecasting. CoRR abs/2007.15531 (2020) - [i19]Yishi Xu, Yingxue Zhang, Wei Guo, Huifeng Guo, Ruiming Tang, Mark Coates:
GraphSAIL: Graph Structure Aware Incremental Learning for Recommender Systems. CoRR abs/2008.13517 (2020) - [i18]Fatemeh Teimury, Bruno Roy, Juan Sebastián Casallas, David MacDonald, Mark Coates:
GraphSeam: Supervised Graph Learning Framework for Semantic UV Mapping. CoRR abs/2011.13748 (2020)
2010 – 2019
- 2019
- [j38]Jun Ye Yu
, Mark J. Coates
, Michael G. Rabbat
:
Graph-Based Compression for Distributed Particle Filters. IEEE Trans. Signal Inf. Process. over Networks 5(3): 404-417 (2019) - [j37]Yunpeng Li
, Soumyasundar Pal
, Mark J. Coates
:
Invertible Particle-Flow-Based Sequential MCMC With Extension to Gaussian Mixture Noise Models. IEEE Trans. Signal Process. 67(9): 2499-2512 (2019) - [c77]Yingxue Zhang, Soumyasundar Pal, Mark Coates, Deniz Üstebay:
Bayesian Graph Convolutional Neural Networks for Semi-Supervised Classification. AAAI 2019: 5829-5836 - [c76]Soumyasundar Pal, Mark Coates:
Particle Flow Particle Filter using Gromov's method. CAMSAP 2019: 634-638 - [c75]Florence Regol, Soumyasundar Pal, Mark Coates:
Node Copying for Protection Against Graph Neural Network Topology Attacks. CAMSAP 2019: 709-713 - [c74]Lena Kranold
, Collin Quintyne, Mark Coates, Milica Popovic:
Microwave Radar for Breast Screening: Initial Clinical Data with Suspicious-Lesion Patients. EMBC 2019: 3191-3194 - [c73]Juliette Valenchon, Mark Coates:
Multiple-graph Recurrent Graph Convolutional Neural Network Architectures for Predicting Disease Outcomes. ICASSP 2019: 3157-3161 - [c72]Soumyasundar Pal, Mark Coates:
Scalable MCMC in Degree Corrected Stochastic Block Model. ICASSP 2019: 5461-5465 - [c71]Jianing Sun, Yingxue Zhang, Chen Ma
, Mark Coates, Huifeng Guo, Ruiming Tang
, Xiuqiang He:
Multi-graph Convolution Collaborative Filtering. ICDM 2019: 1306-1311 - [i17]Cody Mazza-Anthony, Bogdan Mazoure, Mark Coates:
Learning Gaussian Graphical Models with Ordered Weighted L1 Regularization. CoRR abs/1906.02719 (2019) - [i16]Soumyasundar Pal, Florence Regol, Mark J. Coates:
Bayesian Graph Convolutional Neural Networks Using Non-Parametric Graph Learning. CoRR abs/1910.12132 (2019) - [i15]Soumyasundar Pal, Florence Regol, Mark Coates:
Bayesian Graph Convolutional Neural Networks using Node Copying. CoRR abs/1911.04965 (2019) - [i14]Chen Ma, Liheng Ma, Yingxue Zhang, Jianing Sun, Xue Liu, Mark Coates:
Memory Augmented Graph Neural Networks for Sequential Recommendation. CoRR abs/1912.11730 (2019) - 2018
- [c70]Soumyasundar Pal, Mark Coates:
Particle Flow Particle Filter for Gaussian Mixture Noise Models. ICASSP 2018: 4249-4253 - [c69]Peter Henderson, Matthew Vertescher, David Meger
, Mark Coates:
Cost Adaptation for Robust Decentralized Swarm Behaviour. IROS 2018: 4099-4106 - [c68]Soumyasundar Pal, Mark Coates:
Sequential MCMC With The Discrete Bouncy Particle Sampler. SSP 2018: 663-667 - [i13]Yingxue Zhang, Soumyasundar Pal, Mark Coates, Deniz Üstebay:
Bayesian graph convolutional neural networks for semi-supervised classification. CoRR abs/1811.11103 (2018) - 2017
- [j36]Yunpeng Li
, Emily Porter
, Adam Santorelli
, Milica Popovic, Mark Coates:
Microwave breast cancer detection via cost-sensitive ensemble classifiers: Phantom and patient investigation. Biomed. Signal Process. Control. 31: 366-376 (2017) - [j35]Milad Kharratzadeh, Mark Coates:
Semi-parametric order-based generalized multivariate regression. J. Multivar. Anal. 156: 89-102 (2017) - [j34]Shohreh Shaghaghian, Mark Coates:
Online Bayesian Inference of Diffusion Networks. IEEE Trans. Signal Inf. Process. over Networks 3(3): 500-512 (2017) - [j33]Yunpeng Li
, Mark Coates:
Particle Filtering With Invertible Particle Flow. IEEE Trans. Signal Process. 65(15): 4102-4116 (2017) - [j32]Augustin-Alexandru Saucan, Mark J. Coates, Michael G. Rabbat:
A Multisensor Multi-Bernoulli Filter. IEEE Trans. Signal Process. 65(20): 5495-5509 (2017) - [c67]