Efficient CDF Approximations for Normalizing Flows.

Andreas M. Lehrmann Facebook Reality Labs, Pittsburgh, PA, USA Disney Research, Pittsburgh, PA, USA Max Planck Institute for Intelligent Systems, Tübingen, Germany https://la.disneyresearch.com/people/andreas-lehrmann/ https://ps.is.tuebingen.mpg.de/person/alehrmann https://scholar.google.com/citations?user=DM49PecAAAAJ

Chandramouli Shama Sastry Andreas M. Lehrmann Marcus A. Brubaker Alexander Radovic Efficient CDF Approximations for Normalizing Flows. 2022 2022 Trans. Mach. Learn. Res. https://openreview.net/forum?id=LnjclqBl8R db/journals/tmlr/tmlr2022.html#SastryLBR22

Chandramouli Shama Sastry Andreas M. Lehrmann Marcus A. Brubaker Alexander Radovic Efficient CDF Approximations for Normalizing Flows. 2022 abs/2202.11322 CoRR https://arxiv.org/abs/2202.11322 db/journals/corr/corr2202.html#abs-2202-11322

Ruizhi Deng Greg Mori Andreas M. Lehrmann Continuous-time Particle Filtering for Latent Stochastic Differential Equations. 2022 abs/2209.00173 CoRR https://doi.org/10.48550/arXiv.2209.00173 db/journals/corr/corr2209.html#abs-2209-00173

Ruizhi Deng Marcus A. Brubaker Greg Mori Andreas M. Lehrmann Continuous Latent Process Flows. 5162-5173 2021 NeurIPS https://proceedings.neurips.cc/paper/2021/hash/2983e3047c0c730d3b7c022584717f3f-Abstract.html conf/nips/2021 db/conf/nips/neurips2021.html#DengBML21 Polina Zablotskaia Edoardo A. Dominici Leonid Sigal Andreas M. Lehrmann PROVIDE: a probabilistic framework for unsupervised video decomposition. 2019-2028 2021 UAI https://proceedings.mlr.press/v161/zablotskaia21a.html conf/uai/2021 db/conf/uai/uai2021.html#ZablotskaiaDSL21

Ruizhi Deng Marcus A. Brubaker Greg Mori Andreas M. Lehrmann Continuous Latent Process Flows. 2021 abs/2106.15580 CoRR https://arxiv.org/abs/2106.15580 db/journals/corr/corr2106.html#abs-2106-15580

Thomas Nestmeyer Jean-François Lalonde Iain A. Matthews Andreas M. Lehrmann Learning Physics-Guided Face Relighting Under Directional Light. 5123-5132 2020 CVPR https://openaccess.thecvf.com/content_CVPR_2020/html/Nestmeyer_Learning_Physics-Guided_Face_Relighting_Under_Directional_Light_CVPR_2020_paper.html https://doi.org/10.1109/CVPR42600.2020.00517 conf/cvpr/2020 db/conf/cvpr/cvpr2020.html#NestmeyerLML20 Megha Nawhal Mengyao Zhai Andreas M. Lehrmann Leonid Sigal Greg Mori Generating Videos of Zero-Shot Compositions of Actions and Objects. 382-401 2020 ECCV (12) https://doi.org/10.1007/978-3-030-58610-2_23 conf/eccv/2020-12 db/conf/eccv/eccv2020-12.html#NawhalZLSM20 Ruizhi Deng Bo Chang 0002 Marcus A. Brubaker Greg Mori Andreas M. Lehrmann Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows. 2020 NeurIPS https://proceedings.neurips.cc/paper/2020/hash/58c54802a9fb9526cd0923353a34a7ae-Abstract.html conf/nips/2020 db/conf/nips/neurips2020.html#DengCBML20

Ruizhi Deng Bo Chang 0002 Marcus A. Brubaker Greg Mori Andreas M. Lehrmann Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows. 2020 abs/2002.10516 CoRR https://arxiv.org/abs/2002.10516 db/journals/corr/corr2002.html#abs-2002-10516

Polina Zablotskaia Edoardo A. Dominici Leonid Sigal Andreas M. Lehrmann Unsupervised Video Decomposition using Spatio-temporal Iterative Inference. 2020 abs/2006.14727 CoRR https://arxiv.org/abs/2006.14727 db/journals/corr/corr2006.html#abs-2006-14727

Stephen Lombardi Tomas Simon Jason M. Saragih Gabriel Schwartz Andreas M. Lehrmann Yaser Sheikh Neural volumes: learning dynamic renderable volumes from images. 65:1-65:14 2019 38 ACM Trans. Graph. 4 https://doi.org/10.1145/3306346.3323020 db/journals/tog/tog38.html#LombardiSSSLS19

Jiawei He 0001 Yu Gong Joseph Marino Greg Mori Andreas M. Lehrmann Variational Autoencoders with Jointly Optimized Latent Dependency Structure. 2019 ICLR (Poster) https://openreview.net/forum?id=SJgsCjCqt7 conf/iclr/2019 db/conf/iclr/iclr2019.html#HeGMML19

Thomas Nestmeyer Iain A. Matthews Jean-François Lalonde Andreas M. Lehrmann Structural Decompositions for End-to-End Relighting. 2019 abs/1906.03355 CoRR http://arxiv.org/abs/1906.03355 db/journals/corr/corr1906.html#abs-1906-03355

Stephen Lombardi Tomas Simon Jason M. Saragih Gabriel Schwartz Andreas M. Lehrmann Yaser Sheikh Neural Volumes: Learning Dynamic Renderable Volumes from Images. 2019 abs/1906.07751 CoRR http://arxiv.org/abs/1906.07751 db/journals/corr/corr1906.html#abs-1906-07751

Megha Nawhal Mengyao Zhai Andreas M. Lehrmann Leonid Sigal Zero-Shot Generation of Human-Object Interaction Videos. 2019 abs/1912.02401 CoRR http://arxiv.org/abs/1912.02401 db/journals/corr/corr1912.html#abs-1912-02401

Jiawei He 0001 Andreas M. Lehrmann Joseph Marino Greg Mori Leonid Sigal Probabilistic Video Generation Using Holistic Attribute Control. 466-483 2018 ECCV (5) https://doi.org/10.1007/978-3-030-01228-1_28 conf/eccv/2018-5 db/conf/eccv/eccv2018-5.html#HeLMMS18

Jiawei He 0001 Andreas M. Lehrmann Joseph Marino Greg Mori Leonid Sigal Probabilistic Video Generation using Holistic Attribute Control. 2018 abs/1803.08085 CoRR http://arxiv.org/abs/1803.08085 db/journals/corr/corr1803.html#abs-1803-08085

Ziad Al-Halah Andreas M. Lehrmann Leonid Sigal Towards Traversing the Continuous Spectrum of Image Retrieval. 2018 abs/1812.00202 CoRR http://arxiv.org/abs/1812.00202 db/journals/corr/corr1812.html#abs-1812-00202

Paul Hongsuck Seo Andreas M. Lehrmann Bohyung Han Leonid Sigal Visual Reference Resolution using Attention Memory for Visual Dialog. 3719-3729 2017 NIPS https://proceedings.neurips.cc/paper/2017/hash/654ad60ebd1ae29cedc37da04b6b0672-Abstract.html http://papers.nips.cc/paper/6962-visual-reference-resolution-using-attention-memory-for-visual-dialog conf/nips/2017 db/conf/nips/nips2017.html#SeoLHS17 Andreas M. Lehrmann Leonid Sigal Non-parametric Structured Output Networks. 4214-4224 2017 NIPS https://proceedings.neurips.cc/paper/2017/hash/04048aeca2c0f5d84639358008ed2ae7-Abstract.html http://papers.nips.cc/paper/7009-non-parametric-structured-output-networks conf/nips/2017 db/conf/nips/nips2017.html#LehrmannS17

Paul Hongsuck Seo Andreas M. Lehrmann Bohyung Han Leonid Sigal Visual Reference Resolution using Attention Memory for Visual Dialog. 2017 abs/1709.07992 CoRR http://arxiv.org/abs/1709.07992 db/journals/corr/corr1709.html#abs-1709-07992

Andreas M. Lehrmann Non-parametric models for structured data and applications to human bodies and natural scenes. 2016 ETH Zurich, Zürich, Switzerland https://hdl.handle.net/20.500.11850/155938 https://doi.org/10.3929/ethz-a-010780141 https://www.base-search.net/Record/fcafebdbc7045abde79c75ac686f03ba14d0f9d973598b04d6bb04286f22040a base-search.net (ftethz:oai:www.research-collection.ethz.ch:20.500.11850/155938) Andreas M. Lehrmann Peter V. Gehler Sebastian Nowozin Efficient Nonlinear Markov Models for Human Motion. 1314-1321 2014 CVPR https://doi.org/10.1109/CVPR.2014.171 https://doi.ieeecomputersociety.org/10.1109/CVPR.2014.171 conf/cvpr/2014 db/conf/cvpr/cvpr2014.html#LehrmannGN14

Andreas M. Lehrmann Michael Huber 0002 Aydin Can Polatkan Albert Pritzkau Kay Nieselt Visualizing dimensionality reduction of systems biology data. 146-165 2013 27 Data Min. Knowl. Discov. 1 https://doi.org/10.1007/s10618-012-0268-8 https://www.wikidata.org/entity/Q62796420 db/journals/datamine/datamine27.html#LehrmannHPPN13

Andreas M. Lehrmann Peter V. Gehler Sebastian Nowozin A Non-parametric Bayesian Network Prior of Human Pose. 1281-1288 2013 ICCV https://doi.org/10.1109/ICCV.2013.162 https://doi.ieeecomputersociety.org/10.1109/ICCV.2013.162 conf/iccv/2013 db/conf/iccv/iccv2013.html#LehrmannGN13 Ziad Al-Halah Marcus A. Brubaker Bo Chang 0002 Ruizhi Deng Edoardo A. Dominici Peter V. Gehler Yu Gong Bohyung Han Jiawei He 0001 Michael Huber 0002 Jean-François Lalonde Stephen Lombardi Joseph Marino Iain A. Matthews Greg Mori Megha Nawhal Thomas Nestmeyer Kay Nieselt Sebastian Nowozin Aydin Can Polatkan Albert Pritzkau Alexander Radovic Jason M. Saragih Chandramouli Shama Sastry Gabriel Schwartz Hongsuck SeoPaul Hongsuck Seo Yaser Sheikh Leonid Sigal Tomas Simon Polina Zablotskaia Mengyao Zhai