A Non-parametric Bayesian Network Prior of Human Pose. - Andreas M. Lehrmann; Peter V. Gehler; Sebastian Nowozin (ICCV, 2013)

Visualizing dimensionality reduction of systems biology data. - Andreas M. Lehrmann; Michael Huber 002; Aydin Can Polatkan; Albert Pritzkau; Kay Nieselt (Data Min. Knowl. Discov., 2013)

Efficient Nonlinear Markov Models for Human Motion. - Andreas M. Lehrmann; Peter V. Gehler; Sebastian Nowozin (CVPR, 2014)

Non-parametric models for structured data and applications to human bodies and natural scenes. - Andreas M. Lehrmann (2016)

Non-parametric Structured Output Networks. - Andreas M. Lehrmann; Leonid Sigal (NIPS, 2017)

Visual Reference Resolution using Attention Memory for Visual Dialog. - Paul Hongsuck Seo; Andreas M. Lehrmann; Bohyung Han; Leonid Sigal (NIPS, 2017)

Probabilistic Video Generation Using Holistic Attribute Control. - Jiawei He 001; Andreas M. Lehrmann; Joseph Marino; Greg Mori; Leonid Sigal (ECCV (5), 2018)

Towards Traversing the Continuous Spectrum of Image Retrieval. - Ziad Al-Halah; Andreas M. Lehrmann; Leonid Sigal (CoRR, 2018)

Variational Autoencoders with Jointly Optimized Latent Dependency Structure. - Jiawei He 001; Yu Gong; Joseph Marino; Greg Mori; Andreas M. Lehrmann (ICLR (Poster), 2019)

Structural Decompositions for End-to-End Relighting. - Thomas Nestmeyer; Iain A. Matthews; Jean-François Lalonde; Andreas M. Lehrmann (CoRR, 2019)

Zero-Shot Generation of Human-Object Interaction Videos. - Megha Nawhal; Mengyao Zhai; Andreas M. Lehrmann; Leonid Sigal (CoRR, 2019)

Neural volumes: learning dynamic renderable volumes from images. - Stephen Lombardi; Tomas Simon; Jason M. Saragih; Gabriel Schwartz; Andreas M. Lehrmann; Yaser Sheikh (ACM Trans. Graph., 2019)

Learning Physics-Guided Face Relighting Under Directional Light. - Thomas Nestmeyer; Jean-François Lalonde; Iain A. Matthews; Andreas M. Lehrmann (CVPR, 2020)

Generating Videos of Zero-Shot Compositions of Actions and Objects. - Megha Nawhal; Mengyao Zhai; Andreas M. Lehrmann; Leonid Sigal; Greg Mori (ECCV (12), 2020)

Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows. - Ruizhi Deng; Bo Chang 002; Marcus A. Brubaker; Greg Mori; Andreas M. Lehrmann (NeurIPS, 2020)

Unsupervised Video Decomposition using Spatio-temporal Iterative Inference. - Polina Zablotskaia; Edoardo A. Dominici; Leonid Sigal; Andreas M. Lehrmann (CoRR, 2020)

Continuous Latent Process Flows. - Ruizhi Deng; Marcus A. Brubaker; Greg Mori; Andreas M. Lehrmann (NeurIPS, 2021)

PROVIDE: a probabilistic framework for unsupervised video decomposition. - Polina Zablotskaia; Edoardo A. Dominici; Leonid Sigal; Andreas M. Lehrmann (UAI, 2021)

Continuous-time Particle Filtering for Latent Stochastic Differential Equations. - Ruizhi Deng; Greg Mori; Andreas M. Lehrmann (CoRR, 2022)

Efficient CDF Approximations for Normalizing Flows. - Chandramouli Shama Sastry; Andreas M. Lehrmann; Marcus A. Brubaker; Alexander Radovic (Trans. Mach. Learn. Res., 2022)