Andreas M. Lehrmann

Publication Activity (10 Years)

Years Active: 2013-2022
Publications (10 Years): 22

Top Topics

Stochastic Process

Spatio Temporally

Structured Output

Top Venues

Publications

Ruizhi Deng, Greg Mori, Andreas M. Lehrmann
Continuous-time Particle Filtering for Latent Stochastic Differential Equations. CoRR (2022)
Chandramouli Shama Sastry, Andreas M. Lehrmann, Marcus Brubaker, Alexander Radovic
Efficient CDF Approximations for Normalizing Flows. CoRR (2022)
Chandramouli Shama Sastry, Andreas M. Lehrmann, Marcus A. Brubaker, Alexander Radovic
Efficient CDF Approximations for Normalizing Flows. Trans. Mach. Learn. Res. 2022 (2022)
Ruizhi Deng, Marcus A. Brubaker, Greg Mori, Andreas M. Lehrmann
Continuous Latent Process Flows. CoRR (2021)
Polina Zablotskaia, Edoardo A. Dominici, Leonid Sigal, Andreas M. Lehrmann
PROVIDE: a probabilistic framework for unsupervised video decomposition. UAI (2021)
Ruizhi Deng, Marcus A. Brubaker, Greg Mori, Andreas M. Lehrmann
Continuous Latent Process Flows. NeurIPS (2021)
Thomas Nestmeyer, Jean-François Lalonde, Iain A. Matthews, Andreas M. Lehrmann
Learning Physics-Guided Face Relighting Under Directional Light. CVPR (2020)
Megha Nawhal, Mengyao Zhai, Andreas M. Lehrmann, Leonid Sigal, Greg Mori
Generating Videos of Zero-Shot Compositions of Actions and Objects. ECCV (12) (2020)
Ruizhi Deng, Bo Chang, Marcus A. Brubaker, Greg Mori, Andreas M. Lehrmann
Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows. CoRR (2020)
Polina Zablotskaia, Edoardo A. Dominici, Leonid Sigal, Andreas M. Lehrmann
Unsupervised Video Decomposition using Spatio-temporal Iterative Inference. CoRR (2020)
Ruizhi Deng, Bo Chang, Marcus A. Brubaker, Greg Mori, Andreas M. Lehrmann
Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows. NeurIPS (2020)
Stephen Lombardi, Tomas Simon, Jason M. Saragih, Gabriel Schwartz, Andreas M. Lehrmann, Yaser Sheikh
Neural Volumes: Learning Dynamic Renderable Volumes from Images. CoRR (2019)
Jiawei He, Yu Gong, Joseph Marino, Greg Mori, Andreas M. Lehrmann
Variational Autoencoders with Jointly Optimized Latent Dependency Structure. ICLR (Poster) (2019)
Megha Nawhal, Mengyao Zhai, Andreas M. Lehrmann, Leonid Sigal
Zero-Shot Generation of Human-Object Interaction Videos. CoRR (2019)
Stephen Lombardi, Tomas Simon, Jason M. Saragih, Gabriel Schwartz, Andreas M. Lehrmann, Yaser Sheikh
Neural volumes: learning dynamic renderable volumes from images. ACM Trans. Graph. 38 (4) (2019)
Thomas Nestmeyer, Iain A. Matthews, Jean-François Lalonde, Andreas M. Lehrmann
Structural Decompositions for End-to-End Relighting. CoRR (2019)
Jiawei He, Andreas M. Lehrmann, Joseph Marino, Greg Mori, Leonid Sigal
Probabilistic Video Generation Using Holistic Attribute Control. ECCV (5) (2018)
Jiawei He, Andreas M. Lehrmann, Joseph Marino, Greg Mori, Leonid Sigal
Probabilistic Video Generation using Holistic Attribute Control. CoRR (2018)
Ziad Al-Halah, Andreas M. Lehrmann, Leonid Sigal
Towards Traversing the Continuous Spectrum of Image Retrieval. CoRR (2018)
Paul Hongsuck Seo, Andreas M. Lehrmann, Bohyung Han, Leonid Sigal
Visual Reference Resolution using Attention Memory for Visual Dialog. NIPS (2017)
Paul Hongsuck Seo, Andreas M. Lehrmann, Bohyung Han, Leonid Sigal
Visual Reference Resolution using Attention Memory for Visual Dialog. CoRR (2017)
Andreas M. Lehrmann, Leonid Sigal
Non-parametric Structured Output Networks. NIPS (2017)
Andreas M. Lehrmann, Peter V. Gehler, Sebastian Nowozin
Efficient Nonlinear Markov Models for Human Motion. CVPR (2014)
Andreas M. Lehrmann, Peter V. Gehler, Sebastian Nowozin
A Non-parametric Bayesian Network Prior of Human Pose. ICCV (2013)
Andreas M. Lehrmann, Michael Huber, Aydin Can Polatkan, Albert Pritzkau, Kay Nieselt
Visualizing dimensionality reduction of systems biology data. Data Min. Knowl. Discov. 27 (1) (2013)