Publications
Journals
[J17] Carter, J., Chen, X., Cazzola, D., Trewartha, G., & Preatoni, E. (2024). Consumer-priced wearable sensors combined with deep learning can be used to accurately predict ground reaction forces during various treadmill running conditions. PeerJ , 12, e17896. [pdf]
[J16] Li, Y., Li, C., Wei, Y., Price, S., Schönlieb, C. B., & Chen, X.* (2024). Multi-objective Bayesian optimization with enhanced features for adaptively improved glioblastoma partitioning and survival prediction. Computerized Medical Imaging and Graphics , 102420. [pdf]
[J15] Rivadulla, A. R., Chen, X., Cazzola, D., Trewartha, G., & Preatoni, E. (2024). Clustering analysis across different speeds reveals two distinct running techniques with no differences in running economy. Sports Biomechanics, 1-24. [pdf]
[J14] Li, Y. F., Ji, H. B., Chen, X., Yang, Y. L., & Lai, Y. K. (2024). Learning key lines for multi-object tracking. Computer Vision and Image Understanding , 241. [link]
[J13] Tang, T., Ding, H., Dai, S., Chen, X., Taylor, P. H., Zang, J., & Adcock, T. A. (2024). Data informed model test design with machine learning–an example in nonlinear wave load on a vertical cylinder. In Journal of Offshore Mechanics and Arctic Engineering, 146(2). [pdf]
[J12] Tang, T., Ryan, G., Ding, H., Chen, X., Zang, J., Taylor, P., & Adcock, T. (2024). A new Gaussian Process based model for non-linear wave loading on vertical cylinders. Coastal Engineering. [link]
[J11] Wilson, H., Chen, X., Golbabaee, M., Proulx, M. J., & O’Neill, E. (2024). Feasibility of decoding visual information from EEG. Brain-Computer Interfaces, 1-28.[pdf]
[J10] Wei, Y., Chen, X., Zhu, L., Zhang, L., Schönlieb, C. B., Price, S. J., & Li, C. (2023). Multi-modal learning for predicting the genotype of glioma. IEEE Transactions on Medical Imaging. [pdf]
[J9] Li, Y. F., Ji, H. B., Chen, X., Lai, Y. K., & Yang, Y. L. (2023). Multi-object tracking with robust object regression and association. Computer Vision and Image Understanding, 227, 103586. [Link]
[J8] Chen, X., Feroz, F., & Hobson, M. (2023). Bayesian posterior repartitioning for nested sampling. Bayesian Analysis, 1(1), 1-27. [pdf]
[J7] Ashton, G., Barbary, K., Bernstein N., Buchner J., Chen X., Csányi G., Fowlie A., et. al. (2022). Nested Sampling for physical scientists. Nature Reviews: Methods Primers , 2(1), 39. [pdf]
[J6] Gong, X., Chen, X.*, Zhong, Z., & Chen, W. (2021). Enhanced Few-Shot Learning for Intrusion Detection in Railway Video Surveillance. IEEE Transactions on Intelligent Transportation Systems, 23(8), 11301-11313. [pdf]
[J5] Das, S., Hobson, M. P., Feroz, F., Chen, X., Phadke, S., Goudswaard, J., & Hohl, D. (2021). Microseismic event detection in large heterogeneous velocity models using Bayesian multimodal nested sampling. Data-Centric Engineering, 2, e1. [pdf]
[J4] Chen, X., Hobson, M., Das, S., & Gelderblom, P. (2019). Improving the efficiency and robustness of nested sampling using posterior repartitioning. Statistics and Computing, 29, 835-850. [pdf]
[J3] Das, S., Chen, X., Hobson, M. P., et. al. (2018). Surrogate regression modelling for fast seismogram generation and detection of microseismic events in heterogeneous velocity models. Geophysical Journal International, 215(2), 1257-1290. [pdf]
[J2] Das, S., Chen, X., & Hobson, M. P. (2017). Fast GPU-Based seismogram simulation from microseismic events in marine environments using heterogeneous velocity models. IEEE Transactions on Computational Imaging, 3(2), 316-329. [pdf]
[J1] Chen, X., Särkkä, S., & Godsill, S. (2015). A Bayesian particle filtering method for brain source localisation. Digital Signal Processing, 47, 192-204. [pdf]
Conference Proceedings
[C18] Jagpal, D., Chen, X.*, & Namboodiri, V. P. (2025). EIDT-V: Exploiting Intersections in Diffusion Trajectories for Model-Agnostic, Zero-Shot, Training-Free Text-to-Video Generation. In IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR 2025) . (Accepted) [pdf]
[C17] Zhang, J., Yan, R., Perelli, A., Chen, X., & Li, C. (2024). Phy-Diff: Physics-guided Hourglass Diffusion Model for Diffusion MRI Synthesis. In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2024) . [pdf]
[C16] Li, Y., Li, C., Wei, Y., Price, S., Schönlieb, C. B., & Chen, X.* (2023). G-CNN: Adaptive Geometric Convolutional Neural Networks for MRI-Based Skull Stripping. In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023) Workshop on Computational Mathematics Modeling in Cancer Analysis (pp. 21-30). Cham: Springer Nature Switzerland.. [pdf]
[C15] Mao, Y., Jiang, L., Chen, X., & Li, C. (2023). DisC-Diff: Disentangled Conditional Diffusion Model for Multi-Contrast MRI Super-Resolution. In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023). [pdf]
[C14] Jiang, L., Mao, Y., Chen, X., Wang, X., & Li, C. (2023). CoLa-Diff: Conditional Latent Diffusion Model for Multi-Modal MRI Synthesis. In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2023). [pdf]
[C13] Li, C., Huang, W., Chen, X.*, Wei, Y., Price, S. J., & Schönlieb, C. B. (2023). Expectation-Maximization Regularized Deep Learning for Weakly Supervised Tumor Segmentation for Glioblastoma. In IEEE International Symposium on Biomedical Imaging (ISBI). [pdf]
[C12] Wei, Y., Chen, X., Schönlieb, C. B., & Price, S. J., Li, C. (2023). Predicting conversion of mild cognitive impairment to Alzheimer's disease by modelling healthy ageing trajectories. In IEEE International Symposium on Biomedical Imaging (ISBI). [pdf]
[C11] Carter, J., Chen, X., Cazzola, D., Trewartha, G. & Preatoni, E. (2023). Estimation of ground reaction force during running using consumer-level wearable insoles and machine learning. In ISBS Proceedings Archives: 41st International Conference on Biomechanics in Sports. [pdf]
[C10] Wei, Y., Li, C., Chen, X., Schönlieb, C. B., & Price, S. J. (2022). Collaborative learning of images and geometrics for predicting isocitrate dehydrogenase status of glioma. In IEEE International Symposium on Biomedical Imaging (ISBI). [pdf]
[C9] Li, C., Wei, Y., & Chen, X.*, Schonlieb, C. B. (2021) BrainNetGAN: Data augmentation of brain connectivity using generative adversarial network for dementia classification. In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2021) Workshop on Deep Generative Models, and Data Augmentation, Labelling, and Imperfections. Springer, Cham. [pdf]
[C8] Wei, Y., Li, Y., Chen, X., Schönlieb, C. B., Li, C., & Price, S. J. (2021). Predicting isocitrate dehydrogenase mutationstatus in glioma using structural brain networksand graph neural networks. In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2021) Brain Lesion (BrainLes) Workshop. [pdf]
[C7] Li, Y., Li, C., Wei, Y., Price, S., Schönlieb, C. B., & Chen, X.* (2021). Adaptive unsupervised learning with enhanced feature representation for intra-tumor partitioning and survival prediction for glioblastoma. In International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI 2021) Brain Lesion (BrainLes) Workshop. [pdf]
[C6] Ramirez, B. A., Gelderblom, P. P., Eales, A. D., Chen, X., Hobson, M. P., & Esler, K. (2017). Sampling From the Posterior in Reservoir Simulation. In Abu Dhabi International Petroleum Exhibition (ADIPE) & Conference. Society of Petroleum Engineers. [link]
[C5] Chen, X., Särkkä, S., & Godsill, S. (2013). Probabilistic initiation and termination for MEG multiple dipole localization using sequential Monte Carlo methods. In Proceedings of the 16th IEEE International Conference on Information Fusion (Fusion 2013) (pp. 580-587). [link]
[C4] Chen, X., & Godsill, S. (2013). Multiple dipolar sources localization for MEG using Bayesian particle filtering. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2013) (pp. 949-953). [link]
[C3] Edelstein, A., Chen, X., Li, Y., & Rabbat, M. (2011). RSS-based node localization in the presence of attenuating objects. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011) (pp. 3528-3531). [pdf]
[C2] Chen, X., Edelstein, A., Li, Y., Coates, M., Rabbat, M., & Men, A. (2011). Sequential Monte Carlo for simultaneous passive device-free tracking and sensor localization using received signal strength measurements. In Proceedings of the 10th ACM/IEEE International Conference on Information Processing in Sensor Networks (IPSN 2011) (pp. 342-353). [pdf]
[C1] Li, Y., Chen, X.*, Coates, M., & Yang, B. (2011). Sequential Monte Carlo radio-frequency tomographic tracking. In IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP 2011) (pp. 3976-3979). [pdf]
Book chapter
[B1] Lu, Y., Jin, Y., & Chen, X.* (2023) Recombination-based two-stage out-of-distribution detection method for traffic flow pattern analysis. In Handbook on Artificial Intelligence and Transport. Edward Elgar. [link]
