| Memory-based deep reinforcement learning for pomdps L Meng, R Gorbet, D Kulić 2021 IEEE/RSJ international conference on intelligent robots and systems …, 2021 | 115 | 2021 |
| Research on denoising sparse autoencoder L Meng, S Ding, Y Xue International Journal of Machine Learning and Cybernetics 8, 1719-1729, 2017 | 72 | 2017 |
| A density-adaptive affinity propagation clustering algorithm based on spectral dimension reduction H Jia, S Ding, L Meng, S Fan Neural Computing and Applications 25 (7-8), 1557-1567, 2014 | 50 | 2014 |
| The effect of multi-step methods on overestimation in deep reinforcement learning L Meng, R Gorbet, D Kulić 2020 25th International Conference on Pattern Recognition (ICPR), 347-353, 2021 | 40 | 2021 |
| Research of stacked denoising sparse autoencoder L Meng, S Ding, N Zhang, J Zhang Neural Computing and Applications 30, 2083-2100, 2018 | 34 | 2018 |
| A review on feature binding theory and its functions observed in perceptual process S Ding, L Meng, Y Han, Y Xue Cognitive Computation 9, 194-206, 2017 | 23 | 2017 |
| Learning to Engage with Interactive Systems: A Field Study on Deep Reinforcement Learning in a Public Museum L Meng, D Lin, A Francey, R Gorbet, P Beesley, D Kulić ACM Transactions on Human-Robot Interaction 10 (1), 1-29, 2020 | 18* | 2020 |
| Towards individualized affective human-machine interaction K Kumagai, D Lin, L Meng, A Blidaru, P Beesley, D Kulić, I Mizuuchi 2018 27th IEEE International Symposium on Robot and Human Interactive …, 2018 | 7 | 2018 |
| Partial Observability during DRL for Robot Control L Meng, R Gorbet, D Kulić arXiv preprint arXiv:2209.04999, 2022 | 1 | 2022 |
| Detecting near-miss events with cyclists using computer vision approaches B Beck, T Rathnayake, D Kulic, M Li, L Meng, Z Chen, A Cosgun Australasian Road Safety Conference, 2023, Cairns, Queensland, Australia, 2023 | | 2023 |
| Learning to Engage: An Application of Deep Reinforcement Learning in Living Architecture Systems L Meng University of Waterloo, 2023 | | 2023 |
| A Benchmark for Cycling Close Pass Near Miss Event Detection from Video Streams M Li, T Rathnayake, B Beck, L Meng, Z Chen, A Cosgun, X Chang, ... arXiv preprint arXiv:2304.11868, 2023 | | 2023 |
| A Benchmark for Cycling Close Pass Detection from Video Streams M Li, B Beck, T Rathnayake, L Meng, Z Chen, A Cosgun, X Chang Available at SSRN 4773028, 0 | | |
Dana KulićProfessor, Monash University在 monash.edu 的电子邮件经过验证
