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Lazar Atanackovic
Lazar Atanackovic
Ph.D. Candidate at the University of Toronto, Vector Institute
Bestätigte E-Mail-Adresse bei mail.utoronto.ca - Startseite
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Zitiert von
Zitiert von
Jahr
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
592019
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
482024
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
482018
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
202022
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
152024
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
52025
Investigating generalization behaviours of generative flow networks
L Atanackovic, E Bengio
arXiv preprint arXiv:2402.05309, 2024
52024
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
52022
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
52019
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
22020
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
22020
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
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