Selected Publications

This page is intended to highlight some particular topics we have worked on. Complete lists of publications can be found on the Google Scholar links on the home pages of the academic staff.

  • Niwa, K., Takezawa, Y., Zhang, G., Kleijn, W. B. (2025). Revisiting 1-peer exponential graph for enhancing decentralized learning efficiency, The Thirty-ninth Annual Conference on Neural Information Processing Systems (Neurips).
  • A. Lee, A. Gomes, H. M & Zhang. Y, & Kleijn. W. B. (2025). Kolmogorov-Arnold Networks Still Catastrophically Forget but Differently from MLP. Proceedings AAAI Conf. on Artificial Intelligence, vol. 39, no. 17, pp. 18053-18061.
  • Zhang, G., Lewis, J. P., & Kleijn, W. B. (2025). Exact diffusion inversion via bidirectional integration approximation. European Conference on Computer Vision (pp. 19-36). Springer, Cham.
  • Gambetta, D., Gezici, G., Giannotti, F., Pedreschi, D., Knott, A., & Pappalardo, L. (2024). A linguistic analysis of undesirable outcomes in the era of generative AI. arXiv preprint arXiv:2410.12341.
  • Ma, W. D. K., Lewis, J. P., & Kleijn, W. B. (2024, December). Trailblazer: Trajectory control for diffusion-based video generation. SIGGRAPH Asia 2024 Conference Papers (pp. 1-11).
  • Knott, A., Pedreschi, D., Jitsuzumi, T., Leavy, S., Eyers, D., Chakraborti, T., … Russell, S. & Bengio, Y. (2024). AI content detection in the emerging information ecosystem: New obligations for media and tech companies. Ethics and Information Technology, 26(4), 1-14.
  • Ma, W. D. K., Lahiri, A., Lewis, J. P., Leung, T., & Kleijn, W. B. (2024, March). Directed diffusion: Direct control of object placement through attention guidance. In Proceedings of the AAAI Conference on Artificial Intelligence (Vol. 38, No. 5, pp. 4098-4106).
  • Pedreschi, D., Pappalardo, L., Ferragina, E., Baeza-Yates, R., Barabási, A. L., Dignum, F., Dignum, V., Eliasi-Rad, T., Gianotti, F., Kertész, J., Knott, A., ... & Vespignani, A. (2024). Human-AI Coevolution. Artificial Intelligence, 104244.
  • Knott, A., Pedreschi, D., Chatila, R., Chakraborti, T., Leavy, S., Baeza-Yates, R., … Russell, S., & Bengio, Y. (2023). Generative AI models should include detection mechanisms as a condition for public release. Ethics and Information Technology, 25(4), 55.
  • Lee, A., Zhang, Y., Gomes, H M., Bifet, A., Pfahringer, B. (2023). Look At Me, No Replay! SurpriseNet: Anomaly Detection Inspired Class Incremental Learning. Conference on Information and Knowledge Management (CIKM)
  • Robinson, D., Hoong, K., Kleijn, W. B., Doronin, A., Rehbinder, J., Vizet, J., ... & Novikova, T. (2023). Polarimetric imaging for cervical pre-cancer screening aided by machine learning: ex vivo studies. Journal of Biomedical Optics, 28(10), 102904-102904.
  • Jenrungrot, T., Chinen, M., Kleijn, W. B., Skoglund, J., Borsos, Z., Zeghidour, N., & Tagliasacchi, M. (2023, June). Lmcodec: A low bitrate speech codec with causal transformer models. In ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 1-5). IEEE.
  • Lee, A., Zhang, Y., Gomes, H M. (2022). Balancing the Stability Plasticity Dilemma with Online Stability Tuning for Continual Learning. International Joint Conference on Neural Networks (IJCNN).
  • Kleijn, W. B., Storus, A., Chinen, M., Denton, T., Lim, F. S., Luebs, A., ... & Yeh, H. (2021, June). Generative speech coding with predictive variance regularization. In ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) (pp. 6478-6482). IEEE.
  • Yu, W., & Kleijn, W. B. (2020). Room acoustical parameter estimation from room impulse responses using deep neural networks. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 29, 436-447.
  • Niwa, K., Harada, N., Zhang, G., & Kleijn, W. B. (2020, August). Edge-consensus learning: Deep learning on P2P networks with nonhomogeneous data. In Proceedings of the 26th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining (pp. 668-678).
  • Ma, W. D. K., Lewis, J. P., & Kleijn, W. B. (2020, April). The HSIC bottleneck: Deep learning without back-propagation. In Proceedings of the AAAI conference on artificial intelligence (Vol. 34, No. 04, pp. 5085-5092).
  • Van Kuyk, S., Kleijn, W. B., & Hendriks, R. C. (2018). An evaluation of intrusive instrumental intelligibility metrics. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 26(11), 2153-2166.
  • Ma, Z., Lai, Y., Kleijn, W. B., Song, Y. Z., Wang, L., & Guo, J. (2018). Variational Bayesian learning for Dirichlet process mixture of inverted Dirichlet distributions in non-Gaussian image feature modeling. IEEE transactions on neural networks and learning systems, 30(2), 449-463.
  • Balduzzi, D., Frean, M., Leary, L., Lewis, J. P., Ma, K. W. D., & McWilliams, B. (2017, July). The shattered gradients problem: If resnets are the answer, then what is the question?. In International conference on machine learning (pp. 342-350). PMLR.
Print version | Backlinks |