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Mark J. Coates – M. J. Coates
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- affiliation: McGill University, Montreal, Canada
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2020 – today
- 2023
[c110]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- [c109]Florence Regol, Mark Coates:
Diffusing Gaussian Mixtures for Generating Categorical Data. AAAI 2023: 9570-9578 - [c108]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 - [c107]Amur Ghose, Yingxue Zhang, Jianye Hao, Mark Coates:
Spectral Augmentations for Graph Contrastive Learning. AISTATS 2023: 11213-11266 - [c106]Florence Regol, Anja Kroon, Mark Coates:
Evaluation of Categorical Generative Models - Bridging the Gap Between Real and Synthetic Data. ICASSP 2023: 1-5 - [c105]Pavel Rumiantsev, Mark Coates:
Performing Neural Architecture Search Without Gradients. ICASSP 2023: 1-5 - [c104]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 - [c103]Can Chen, Yingxue Zhang, Xue Liu, Mark Coates:
Bidirectional Learning for Offline Model-based Biological Sequence Design. ICML 2023: 5351-5366 - [c102]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 - [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]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 - [i12]Peter Henderson, Matthew Vertescher, David Meger, Mark Coates:
Cost Adaptation for Robust Decentralized Swarm Behaviour. CoRR abs/1709.07114 (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) - [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 - [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
- [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) - [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 - [i9]Shohreh Shaghaghian, Mark Coates:
Optimal Forwarding in Opportunistic Delay Tolerant Networks with Meeting Rate Estimations. CoRR abs/1506.04729 (2015) - 2014
- [c50]Arslan Shahid, Deniz Üstebay, Mark Coates:
Distributed ensemble Kalman filtering. SAM 2014: 217-220 - [c49]