| Neural Volumes: Learning Dynamic Renderable Volumes from Images S Lombardi, T Simon, J Saragih, G Schwartz, AM Lehrmann, Y Sheikh Transactions on Graphics (TOG), 2019 | 366 | 2019 |
| Efficient Nonlinear Markov Models for Human Motion AM Lehrmann, PV Gehler, S Nowozin Computer Vision and Pattern Recognition (CVPR), 2014 | 129 | 2014 |
| Visual Reference Resolution using Attention Memory for Visual Dialog PH Seo, AM Lehrmann, B Han, L Sigal Advances in Neural Information Processing Systems (NeurIPS), 2017 | 96 | 2017 |
| Probabilistic Video Generation using Holistic Attribute Control J He, AM Lehrmann, J Marino, G Mori, L Sigal European Conference on Computer Vision (ECCV), 2018 | 63 | 2018 |
| Learning Physics-guided Face Relighting under Directional Light T Nestmeyer, JF Lalonde, I Matthews, AM Lehrmann Computer Vision and Pattern Recognition (CVPR), 2020 | 51 | 2020 |
| A Non-parametric Bayesian Network Prior of Human Pose AM Lehrmann, PV Gehler, S Nowozin International Conference on Computer Vision (ICCV), 2013 | 47 | 2013 |
| Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows R Deng, B Chang, MA Brubaker, G Mori, A Lehrmann Advances in Neural Information Processing Systems (NeurIPS), 2020 | 19 | 2020 |
| PROVIDE: A Probabilistic Framework for Unsupervised Video Decomposition P Zablotskaia, EA Dominici, L Sigal, AM Lehrmann Uncertainty in Artificial Intelligence (UAI), 2021 | 12* | 2021 |
| Generating Videos of Zero-Shot Compositions of Actions and Objects M Nawhal, M Zhai, A Lehrmann, L Sigal, G Mori European Conference on Computer Vision (ECCV), 2020 | 11* | 2020 |
| Variational Autoencoders with Jointly Optimized Latent Dependency Structure J He, Y Gong, J Marino, G Mori, AM Lehrmann International Conference on Learning Representations (ICLR), 2018 | 10 | 2018 |
| Visualizing Dimensionality Reduction of Systems Biology Data AM Lehrmann, M Huber, AC Polatkan, A Pritzkau, K Nieselt Data Mining and Knowledge Discovery, 2013 | 10 | 2013 |
| Non-parametric Structured Output Networks AM Lehrmann, L Sigal Advances in Neural Information Processing Systems (NeurIPS), 2017 | 4 | 2017 |
| Continuous Latent Process Flows R Deng, MA Brubaker, G Mori, A Lehrmann Advances in Neural Information Processing Systems 34, 5162-5173, 2021 | 2 | 2021 |
| Visual Reference Resolution using Attention Memory for Visual Dialog AM Lehrmann, PH Seo US Patent App. 15/884,339, 2019 | 2 | 2019 |
| Agent Forecasting at Flexible Horizons using ODE Flows A Radovic, J He, J Ramanan, MA Brubaker, A Lehrmann ICML Workshop on Invertible Neural Networks, Normalizing Flows, and Explicit …, 2021 | 1 | 2021 |
| Traversing the Continuous Spectrum of Image Retrieval with Deep Dynamic Models Z Al-Halah, AM Lehrmann, L Sigal arXiv preprint arXiv:1812.00202, 2018 | 1* | 2018 |
| Efficient CDF Approximations for Normalizing Flows CS Sastry, A Lehrmann, M Brubaker, A Radovic arXiv preprint arXiv:2202.11322, 2022 | | 2022 |
| Efficient CDF Approximations for Normalizing Flows C Shama Sastry, A Lehrmann, M Brubaker, A Radovic arXiv e-prints, arXiv: 2202.11322, 2022 | | 2022 |
| System and method for unsupervised scene decomposition using spatio-temporal iterative inference P Zablotskaia, ASM LEHRMANN US Patent App. 17/336,898, 2021 | | 2021 |
| Systems and methods for modeling continuous stochastic processes with dynamic normalizing flows D Ruizhi, B Chang, MA Brubaker, GP Mori, ASM Lehrmann US Patent App. 17/170,416, 2021 | | 2021 |
Leonid SigalAssociate Professor, University of British ColumbiaE-mail confirmado em cs.ubc.ca
