| Cable diagnostics with power line modems for smart grid monitoring Y Huo, G Prasad, L Atanackovic, L Lampe, VCM Leung IEEE Access 7, 60206-60220, 2019 | 59 | 2019 |
| Simulation-free schrödinger bridges via score and flow matching A Tong, N Malkin, K Fatras, L Atanackovic, Y Zhang, G Huguet, G Wolf, ... International Conference on Artificial Intelligence and Statistics (AISTATS), 2024 | 50 | 2024 |
| Grid surveillance and diagnostics using power line communications Y Huo, G Prasad, L Atanackovic, L Lampe, VCM Leung IEEE ISPLC, Best Student Paper Award, 1-6, 2018 | 48 | 2018 |
| DynGFN: Towards Bayesian Inference of Gene Regulatory Networks with GFlowNets L Atanackovic, A Tong, B Wang, LJ Lee, Y Bengio, JS Hartford Advances in Neural Information Processing Systems (NeurIPS) 36, 2023 | 33* | 2023 |
| A graph neural network approach for molecule carcinogenicity prediction P Fradkin, A Young, L Atanackovic, B Frey, LJ Lee, B Wang Bioinformatics 38, i84-i91, 2022 | 20 | 2022 |
| A computational framework for solving Wasserstein Lagrangian flows K Neklyudov, R Brekelmans, A Tong, L Atanackovic, Q Liu, A Makhzani International Conference on Machine Learning (ICML), 2024 | 15 | 2024 |
| The Superposition of Diffusion Models Using the Itô Density Estimator M Skreta, L Atanackovic, AJ Bose, A Tong, K Neklyudov International Conference on Learning Representations (ICLR), Spotlight, 2025 | 5* | 2025 |
| Meta flow matching: Integrating vector fields on the wasserstein manifold L Atanackovic, X Zhang, B Amos, M Blanchette, LJ Lee, Y Bengio, A Tong, ... International Conference on Learning Representations (ICLR), 2025 | 5 | 2025 |
| Investigating generalization behaviours of generative flow networks L Atanackovic, E Bengio arXiv preprint arXiv:2402.05309, 2024 | 5 | 2024 |
| Robustness to adversarial gradients: A glimpse into the loss landscape of contrastive pre-training P Fradkin, L Atanackovic, MR Zhang ICML Workshop on Pre-training: Perspectives, Pitfalls, and Paths Forward, 2022 | 5 | 2022 |
| Statistical shipping noise characterization and mitigation for underwater acoustic communications L Atanackovic, R Zhang, L Lampe, R Diamant IEEE OCEANS 2019-Marseille, 1-7, 2019 | 5 | 2019 |
| Stochastic ship-radiated noise modelling via generative adversarial networks L Atanackovic, V Vakilian, D Wiebe, L Lampe, R Diamant IEEE Global OCEANS 2020: Singapore–US gulf coast, 1-8, 2020 | 2 | 2020 |
| Deep-learning based ship-radiated noise suppression for underwater acoustic OFDM systems L Atanackovic, L Lampe, R Diamant IEEE Global OCEANS 2020: Singapore–US Gulf Coast, 1-8, 2020 | 2 | 2020 |
| Energy-based Modelling for Single-cell Data Annotation T Liu, P Fradkin, L Atanackovic, LJ Lee Machine Learning in Computational Biology, 94-109, 2022 | | 2022 |
| Machine learning inspired ship-radiated noise modelling and cancellation for underwater acoustic communication systems L Atanackovic University of British Columbia, 2020 | | 2020 |
| Curly Flow Matching for Learning Non-gradient Field Dynamics K Petrović, L Atanackovic, K Kapusniak, MM Bronstein, J Bose, A Tong ICLR 2025 Workshop on Machine Learning for Genomics Explorations, 0 | | |
Alexander TongMila; Université de MontréalVerified email at mila.quebec
