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ORCIDMark Coates
Mark J. Coates – M. J. Coates
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- affiliation: McGill University, Montreal, Canada
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Journal Articles
- 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) - 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) - 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) - 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) - 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) - 2016
- [j31]Jun Ye Yu, Mark J. Coates, Michael G. Rabbat, Stéphane Blouin:
A Distributed Particle Filter for Bearings-Only Tracking on Spherical Surfaces. IEEE Signal Process. Lett. 23(3): 326-330 (2016) - [j30]Santosh Nannuru, Stéphane Blouin, Mark Coates, Michael G. Rabbat:
Multisensor CPHD filter. IEEE Trans. Aerosp. Electron. Syst. 52(4): 1834-1854 (2016) - [j29]Emily Porter, Mark Coates, Milica Popovic:
An Early Clinical Study of Time-Domain Microwave Radar for Breast Health Monitoring. IEEE Trans. Biomed. Eng. 63(3): 530-539 (2016) - 2015
- [j28]Milad Kharratzadeh, Benjamin Renard, Mark J. Coates:
Bayesian topic model approaches to online and time-dependent clustering. Digit. Signal Process. 47: 25-35 (2015) - [j27]Santosh Nannuru, Mark Coates:
Hybrid multi-Bernoulli and CPHD filters for superpositional sensors. IEEE Trans. Aerosp. Electron. Syst. 51(4): 2847-2863 (2015) - [j26]Shohreh Shaghaghian, Mark Coates:
Optimal Forwarding in Opportunistic Delay Tolerant Networks With Meeting Rate Estimations. IEEE Trans. Signal Inf. Process. over Networks 1(2): 104-116 (2015) - [j25]Syamantak Datta Gupta, Mark Coates, Michael G. Rabbat:
Error Propagation in Gossip-Based Distributed Particle Filters. IEEE Trans. Signal Inf. Process. over Networks 1(3): 148-163 (2015) - 2013
- [j24]Santosh Nannuru, Mark Coates, Ronald P. S. Mahler:
Computationally-Tractable Approximate PHD and CPHD Filters for Superpositional Sensors. IEEE J. Sel. Top. Signal Process. 7(3): 410-420 (2013) - [j23]Evgeny Kirshin, Boris N. Oreshkin, Kevin Guangran Zhu, Milica Popovic, Mark Coates:
Microwave Radar and Microwave-Induced Thermoacoustics: Dual-Modality Approach for Breast Cancer Detection. IEEE Trans. Biomed. Eng. 60(2): 354-360 (2013) - [j22]Santosh Nannuru, Yunpeng Li, Yan Zeng, Mark Coates, Bo Yang:
Radio-Frequency Tomography for Passive Indoor Multitarget Tracking. IEEE Trans. Mob. Comput. 12(12): 2322-2333 (2013) - 2012
- [j21]Seyed Salim Tabatabaei, Mark Coates, Michael G. Rabbat:
GANC: Greedy agglomerative normalized cut for graph clustering. Pattern Recognit. 45(2): 831-843 (2012) - 2011
- [j20]Frederic Thouin, Mark Coates, Michael G. Rabbat:
Large scale probabilistic available bandwidth estimation. Comput. Networks 55(9): 2065-2078 (2011) - [j19]Yvan Pointurier, Mark Coates, Michael G. Rabbat:
Cross-Layer Monitoring in Transparent Optical Networks. JOCN 3(3): 189-198 (2011) - [j18]Anna Scaglione, Mark Coates, Michael Gastpar, John N. Tsitsiklis, Martin Vetterli:
Introduction to the Issue on Gossiping Algorithms Design and Applications. IEEE J. Sel. Top. Signal Process. 5(4): 645-648 (2011) - [j17]Boris N. Oreshkin, Xuan Liu, M. J. Coates:
Efficient Delay-Tolerant Particle Filtering. IEEE Trans. Signal Process. 59(7): 3369-3381 (2011) - 2010
- [j16]Boris N. Oreshkin, Mark Coates, Michael G. Rabbat:
Optimization and analysis of distributed averaging with short node memory. IEEE Trans. Signal Process. 58(5): 2850-2865 (2010) - [j15]Deniz Üstebay, Boris N. Oreshkin, Mark Coates, Michael G. Rabbat:
Greedy gossip with eavesdropping. IEEE Trans. Signal Process. 58(7): 3765-3776 (2010) - 2009
- [j14]Nahid Saberi, Mark Coates:
Scheduling in overlaid star all-photonic networks with large propagation delays. Photonic Netw. Commun. 17(2): 157-169 (2009) - [j13]Tuncer C. Aysal, Boris N. Oreshkin, M. J. Coates:
Accelerated Distributed Average Consensus via Localized Node State Prediction. IEEE Trans. Signal Process. 57(4): 1563-1576 (2009) - 2008
- [j12]Frederic Thouin, Mark Coates:
Equipment allocation in video-on-demand network deployments. ACM Trans. Multim. Comput. Commun. Appl. 5(1): 5:1-5:22 (2008) - [j11]Tuncer C. Aysal, Mark Coates, Michael G. Rabbat:
Distributed Average Consensus With Dithered Quantization. IEEE Trans. Signal Process. 56(10-1): 4905-4918 (2008) - 2007
- [j10]Frederic Thouin, Mark Coates:
Video-on-Demand Networks: Design Approaches and Future Challenges. IEEE Netw. 21(2): 42-48 (2007) - 2006
- [j9]Michael G. Rabbat, Mark Coates, Robert D. Nowak:
Multiple-Source Internet Tomography. IEEE J. Sel. Areas Commun. 24(12): 2221-2234 (2006) - [j8]Richard W. Thommes, Mark Coates:
Deterministic packet marking for time-varying congestion price estimation. IEEE/ACM Trans. Netw. 14(3): 592-602 (2006) - 2004
- [j7]Rui M. Castro, Mark Coates, Robert D. Nowak:
Likelihood based hierarchical clustering. IEEE Trans. Signal Process. 52(8): 2308-2321 (2004) - 2003
- [j6]Yolanda Tsang, Mark Coates, Robert D. Nowak:
Network delay tomography. IEEE Trans. Signal Process. 51(8): 2125-2136 (2003) - 2002
- [j5]M. J. Coates, Ercan E. Kuruoglu:
Time-frequency-based detection in impulsive noise environments using alpha-stable noise models. Signal Process. 82(12): 1917-1925 (2002) - [j4]Mark Coates, Alfred O. Hero III, Robert D. Nowak, Bin Yu:
Internet tomography. IEEE Signal Process. Mag. 19(3): 47-65 (2002) - [j3]Mark Coates, Robert D. Nowak:
Sequential Monte Carlo inference of internal delays in nonstationary data networks. IEEE Trans. Signal Process. 50(2): 366-376 (2002) - 2001
- [j2]Richard G. Baraniuk, Mark Coates, Philippe Steeghs:
Hybrid linear/quadratic time-frequency attributes. IEEE Trans. Signal Process. 49(4): 760-766 (2001) - 1999
- [j1]M. J. Coates, William J. Fitzgerald:
Regionally optimised time-frequency distributions using finite mixture models. Signal Process. 77(3): 247-260 (1999)
Conference and Workshop Papers
- 2024
- [c118]Florence Regol, Mark Coates:
Categorical Generative Model Evaluation via Synthetic Distribution Coarsening. AISTATS 2024: 910-918 - [c117]Yitian Zhang, Liheng Ma, Soumyasundar Pal, Yingxue Zhang, Mark Coates:
Multi-resolution Time-Series Transformer for Long-term Forecasting. AISTATS 2024: 4222-4230 - [c116]Florence Regol, Joud Chataoui, Mark Coates:
Jointly-Learned Exit and Inference for a Dynamic Neural Network. ICLR 2024 - [c115]Liheng Ma, Soumyasundar Pal, Yitian Zhang, Jiaming Zhou, Yingxue Zhang, Mark Coates:
CKGConv: General Graph Convolution with Continuous Kernels. ICML 2024 - [c114]Mai Zeng, Florence Regol, Mark Coates:
Interacting Diffusion Processes for Event Sequence Forecasting. ICML 2024 - [c113]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 - 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 - 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 - 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 - 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 - 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 - 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 - 2017
- [c67]Soumyasundar Pal, Mark Coates:
Gaussian sum particle flow filter. CAMSAP 2017: 1-5 - [c66]Jun Ye Yu, Augustin-Alexandru Saucan, Mark Coates, Michael G. Rabbat:
Algorithms for the multi-sensor assignment problem in the δ-generalized labeled multi-Bernoulli filter. CAMSAP 2017: 1-5 - [c65]Yunpeng Li, Mark Coates:
Sequential MCMC with invertible particle flow. ICASSP 2017: 3844-3848 - [c64]Augustin-Alexandru Saucan, Yunpeng Li, Mark Coates:
Particle flow SMC delta-GLMB filter. ICASSP 2017: 4381-4385 - 2016
- [c63]Michael G. Rabbat, Mark Coates, Stéphane Blouin:
Graph Laplacian distributed particle filtering. EUSIPCO 2016: 1493-1497 - [c62]Yunpeng Li, Mark Coates:
Fast particle flow particle filters via clustering. FUSION 2016: 2022-2027 - [c61]Jun Ye Yu, Mark Coates, Michael G. Rabbat:
Distributed multi-sensor CPHD filter using pairwise gossiping. ICASSP 2016: 3176-3180 - [c60]Yunpeng Li, Lingling Zhao, Mark Coates:
Particle flow for particle filtering. ICASSP 2016: 3979-3983 - [c59]Milad Kharratzadeh, Mark Coates:
Sparse multivariate factor regression. SSP 2016: 1-5 - [c58]Milad Kharratzadeh, Mark Coates:
Order-based generalized multivariate regression. SSP 2016: 1-5 - [c57]Shohreh Shaghaghian, Mark Coates:
Bayesian inference of diffusion networks with unknown infection times. SSP 2016: 1-5 - 2015
- [c56]Yunpeng Li, Lingling Zhao, Mark Coates:
Particle flow auxiliary particle filter. CAMSAP 2015: 157-160 - [c55]Jun Ye Yu, Michael G. Rabbat, Mark Coates, Stéphane Blouin:
Performance investigation on constraint sufficient statistics distributed particle filter. CCECE 2015: 1526-1531 - [c54]Syamantak Datta Gupta, Jun Ye Yu, Mahendra Mallick, Mark Coates, Mark R. Morelande:
Comparison of angle-only filtering algorithms in 3D using EKF, UKF, PF, PFF, and ensemble KF. FUSION 2015: 1649-1656 - [c53]Yunpeng Li, Adam Santorelli, Olivier Laforest, Mark Coates:
Cost-sensitive ensemble classifiers for microwave breast cancer detection. ICASSP 2015: 952-956 - [c52]Benjamin Renard, Milad Kharratzadeh, Mark Coates:
Online time-dependent clustering using probabilistic topic models. ICASSP 2015: 2036-2040 - [c51]Santosh Nannuru, Mark Coates, Michael G. Rabbat, Stéphane Blouin:
General solution and approximate implementation of the multisensor multitarget CPHD filter. ICASSP 2015: 4055-4059 - 2014
- [c50]Arslan Shahid, Deniz Üstebay, Mark Coates:
Distributed ensemble Kalman filtering. SAM 2014: 217-220 - [c49]Shohreh Shaghaghian, Mark Coates:
Opportunistic networks: Minimizing expected latency. WiMob 2014: 473-478 - 2013
- [c48]Jun Ye Yu, Deniz Üstebay, Stéphane Blouin, Michael G. Rabbat, Mark Coates:
Distributed underwater acoustic source localization and tracking. ACSSC 2013: 634-638 - [c47]Santosh Nannuru, Mark Coates:
Particle filter implementation of the multi-Bernoulli filter for superpositional sensors. CAMSAP 2013: 368-371 - [c46]Santosh Nannuru, Mark Coates:
Multi-Bernoulli filter for superpositional sensors. FUSION 2013: 1632-1637 - [c45]Divya Alok Sharma, Mark Coates:
Contact graph based routing in opportunistic networks. GlobalSIP 2013: 333-336 - 2012
- [c44]Muhammad Rizwan Butt, Oscar Delgado, Mark Coates:
An energy-efficiency assessment of Content Centric Networking (CCN). CCECE 2012: 1-4 - [c43]Simone Angela Winkler, Emily Porter, Adam Santorelli, Mark Coates, Milica Popovic:
Recent progress in ultra-wideband microwave breast cancer detection. ICUWB 2012: 182-186 - [c42]Milad Kharratzadeh, Mark Coates:
Weblog Analysis for Predicting Correlations in Stock Price Evolutions. ICWSM 2012 - [c41]Tao Ding, Mark J. Coates:
Implementation of the Daum-Huang exact-flow particle filter. SSP 2012: 257-260 - 2011
- [c40]Frederic Thouin, Santosh Nannuru, Mark Coates:
Multi-target tracking for measurement models with additive contributions. FUSION 2011: 1-8 - [c39]Deniz Üstebay, Mark Coates, Michael G. Rabbat:
Distributed auxiliary particle filters using selective gossip. ICASSP 2011: 3296-3299 - [c38]Yunpeng Li, Xi Chen, Mark Coates, Bo Yang:
Sequential Monte Carlo Radio-Frequency tomographic tracking. ICASSP 2011: 3976-3979 - [c37]Xi Chen, Andrea Edelstein, Yunpeng Li, Mark Coates, Michael G. Rabbat, Aidong Men:
Sequential Monte Carlo for simultaneous passive device-free tracking and sensor localization using received signal strength measurements. IPSN 2011: 342-353 - [c36]Evgeny Kirshin, Boris N. Oreshkin, Kevin Guangran Zhu, Milica Popovic, Mark Coates:
Fusing microwave radar and microwave-induced thermoacoustics for breast cancer detection. ISBI 2011: 113-116 - 2010
- [c35]Xuan Liu, Boris N. Oreshkin, M. J. Coates:
Efficient delay-tolerant particle filtering through selective processing of out-of-sequence measurements. FUSION 2010: 1-8 - [c34]Boris N. Oreshkin, M. J. Coates:
Asynchronous distributed particle filter via decentralized evaluation of Gaussian products. FUSION 2010: 1-8 - 2009
- [c33]Boris N. Oreshkin, Mark J. Coates, Michael G. Rabbat:
Optimization and analysis of distributed averaging with memory. Allerton 2009: 347-354 - [c32]Deniz Üstebay, Boris N. Oreshkin, Mark Coates, Michael G. Rabbat:
Multi-hop Greedy Gossip with Eavesdropping. FUSION 2009: 140-145 - [c31]Deniz Üstebay, Boris N. Oreshkin, Mark Coates, Michael G. Rabbat:
The speed of greed: Characterizing myopic gossip through network voracity. ICASSP 2009: 3665-3668 - [c30]Daniel Nechay, Yvan Pointurier, Mark Coates:
Controlling False Alarm/Discovery Rates in Online Internet Traffic Flow Classification. INFOCOM 2009: 684-692 - 2008
- [c29]Deniz Üstebay, Boris N. Oreshkin, Mark Coates, Michael G. Rabbat:
Rates of convergence for greedy gossip with eavesdropping. Allerton 2008: 367-374 - [c28]Boris N. Oreshkin, Mark Coates:
Weak sense Lp error bounds for leader-node distributed particle filters. FUSION 2008: 1-7 - [c27]Frederic Thouin, Mark Coates, Brian Eriksson, Robert D. Nowak, Clayton D. Scott:
Learning to satisfy. ICASSP 2008: 1981-1984 - [c26]Boris N. Oreshkin, Tuncer C. Aysal, Mark Coates:
Distributed average consensus with increased convergence rate. ICASSP 2008: 2285-2288 - [c25]Deniz Üstebay, Mark Coates, Michael G. Rabbat:
Greedy gossip with eavesdropping. ISWPC 2008: 759-763 - 2007
- [c24]Mark Coates, Yvan Pointurier, Michael G. Rabbat:
Compressed network monitoring for ip and all-optical networks. Internet Measurement Conference 2007: 241-252 - [c23]Tarem Ahmed, Mark Coates, Anukool Lakhina:
Multivariate Online Anomaly Detection Using Kernel Recursive Least Squares. INFOCOM 2007: 625-633 - [c22]Nahid Saberi, Mark Coates:
Feedback Control System for Scheduling of Wide-Area All-Photonic Networks. ISCC 2007: 115-120 - [c21]Frederic Thouin, Mark Coates:
Video-on-Demand Server Selection and Placement. ITC 2007: 18-29 - 2006
- [c20]Nahid Saberi, Mark Coates:
Minimum Rejection Scheduling in All-Photonic Networks. BROADNETS 2006 - [c19]Richard W. Thommes, Mark Coates:
Epidemiological Modelling of Peer-to-Peer Viruses and Pollution. INFOCOM 2006 - [c18]Frederic Thouin, Richard W. Thommes, Mark J. Coates:
Optimal Actuation Strategies for Sensor/Actuator Networks. MobiQuitous 2006: 1-8 - [c17]Frederic Thouin, Mark Coates, Dominic Goodwill:
Video-on-Demand Equipment Allocation. NCA 2006: 103-110 - [c16]Nahid Saberi, Mark Coates:
Fair Matching Algorithm: Fixed-Length Frame Scheduling in All-Photonic Networks. Wireless and Optical Communications 2006: 213-218 - 2005
- [c15]Mark Coates:
Evaluating causal relationships in wireless sensor/actuator networks. ICASSP (5) 2005: 937-940 - 2004
- [c14]Mark Coates, Ioannis N. Psaromiligkos:
Evaluating average causal effect using wireless sensor networks. ICASSP (3) 2004: 905-908 - [c13]Michael G. Rabbat, Robert D. Nowak, Mark Coates:
Multiple Source, Multiple Destination Network Tomography. INFOCOM 2004: 1628-1639 - [c12]Richard W. Thommes, Mark Coates:
Deterministic Packet Marking for Congestion Price Estimation. INFOCOM 2004 - [c11]Mark Coates:
Distributed particle filters for sensor networks. IPSN 2004: 99-107 - 2003
- [c10]Mark Coates, Michael G. Rabbat, Robert D. Nowak:
Merging logical topologies using end-to-end measurements. Internet Measurement Conference 2003: 192-203 - 2002
- [c9]Yolanda Tsang, Mark Coates, Robert D. Nowak:
Nonparametric internet tomography. ICASSP 2002: 2045-2048 - [c8]Mark Coates, Rui M. Castro, Robert D. Nowak, Manik Gadhiok, Ryan King, Yolanda Tsang:
Maximum likelihood network topology identification from edge-based unicast measurements. SIGMETRICS 2002: 11-20 - 2001
- [c7]Yolanda Tsang, Mark Coates, Robert D. Nowak:
Passive network tomography using EM algorithms. ICASSP 2001: 1469-1472 - [c6]Mark Coates, Robert D. Nowak:
Network tomography for internal delay estimation. ICASSP 2001: 3409-3412 - 2000
- [c5]Mark Coates, William J. Fitzgerald:
Time-frequency signal decomposition using energy mixture models. ICASSP 2000: 633-636 - [c4]Richard G. Baraniuk, Mark Coates, Philippe Steeghs:
Hybrid linear/quadratic time-frequency attributes. ICASSP 2000: 681-684 - [c3]Rutger L. van Spaendonck, Felix C. A. Fernandes, Mark Coates, C. Sidney Burrus:
Non-Redundant, Directionally Selective, Complex Wavelets. ICIP 2000: 379-382 - 1999
- [c2]Mark J. Coates, Arnaud Doucet:
Sequential Bayesian wavelet denoising. ISSPA 1999: 595-598 - 1998
- [c1]Mark J. Coates, Christophe G. Molina, William J. Fitzgerald:
Regionally optimised kernels for time-frequency distributions. ICASSP 1998: 1553-1556
Editorship
- 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]
Informal and Other Publications
- 2024
- [i56]Antonios Valkanas, Yuening Wang, Yingxue Zhang, Mark Coates:
Personalized Negative Reservoir for Incremental Learning in Recommender Systems. CoRR abs/2403.03993 (2024) - [i55]Liheng Ma, Soumyasundar Pal, Yitian Zhang, Jiaming Zhou, Yingxue Zhang, Mark Coates:
CKGConv: General Graph Convolution with Continuous Kernels. CoRR abs/2404.13604 (2024) - [i54]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) - [i53]Antonios Valkanas, Boris N. Oreshkin, Mark Coates:
MODL: Multilearner Online Deep Learning. CoRR abs/2405.18281 (2024) - [i52]Pavel Rumiantsev, Mark Coates:
Graph Knowledge Distillation to Mixture of Experts. CoRR abs/2406.11919 (2024) - [i51]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) - 2023
- [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
- [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
- [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
- [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) - 2019
- [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
- [i13]Yingxue Zhang, Soumyasundar Pal, Mark Coates, Deniz Üstebay:
Bayesian graph convolutional neural networks for semi-supervised classification. CoRR abs/1811.11103 (2018) - 2017
- [i12]Peter Henderson, Matthew Vertescher, David Meger, Mark Coates:
Cost Adaptation for Robust Decentralized Swarm Behaviour. CoRR abs/1709.07114 (2017) - 2016
- [i11]Shohreh Shaghaghian, Mark Coates:
Bayesian Inference of Diffusion Networks with Unknown Infection Times. CoRR abs/1602.08114 (2016) - [i10]Shohreh Shaghaghian, Mark Coates:
Online Bayesian Inference of Diffusion Networks. CoRR abs/1611.01086 (2016) - 2015
- [i9]Shohreh Shaghaghian, Mark Coates:
Optimal Forwarding in Opportunistic Delay Tolerant Networks with Meeting Rate Estimations. CoRR abs/1506.04729 (2015) - 2013
- [i8]Syed Haani Masood, Syed Ali Raza, Mark Coates:
Content Distribution Strategies in Opportunistic Networks. CoRR abs/1308.0786 (2013) - 2011
- [i7]Seyed Salim Tabatabaei, Mark Coates, Michael G. Rabbat:
GANC: Greedy Agglomerative Normalized Cut. CoRR abs/1105.0974 (2011) - 2010
- [i6]Frederic Thouin, Mark Coates, Michael G. Rabbat:
Multi-path Probabilistic Available Bandwidth Estimation through Bayesian Active Learning. CoRR abs/1001.1009 (2010) - [i5]Frederic Thouin, Mark Coates, Michael G. Rabbat:
Large scale probabilistic available bandwidth estimation. CoRR abs/1007.0730 (2010) - [i4]Boris N. Oreshkin, Xuan Liu, Mark Coates:
Efficient delay-tolerant particle filtering. CoRR abs/1009.4409 (2010) - [i3]Frederic Thouin, Mark Coates, Michael G. Rabbat:
Real-Time Multi-path Tracking of Probabilistic Available Bandwidth. CoRR abs/1010.1524 (2010) - 2009
- [i2]Boris N. Oreshkin, Mark Coates, Michael G. Rabbat:
Optimization and Analysis of Distributed Averaging with Short Node Memory. CoRR abs/0903.3537 (2009) - [i1]Deniz Üstebay, Boris N. Oreshkin, Mark Coates, Michael G. Rabbat:
Greedy Gossip with Eavesdropping. CoRR abs/0909.1830 (2009)
Coauthor Index
[j43] [j41] [c117] [c115] [c113] [c112] [c110] [c109] [c105] [c104] [c99] [c96] [c95] [c93] [c92] [c91] [c90] [c89] [c88] [c87] [c85] [c83] [c82] [c81] [c80] [c78] [c77] [c71] [i56] [i55] [i54] [i50] [i49] [i48] [i46] [i41] [i36] [i35] [i34] [i31] [i30] [i29] [i28] [i27] [i26] [i25] [i24] [i23] [i22] [i19] [i14] [i13]
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