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Andreas M. Lehrmann
Andreas M. Lehrmann
Facebook Reality Labs
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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
3662019
Efficient Nonlinear Markov Models for Human Motion
AM Lehrmann, PV Gehler, S Nowozin
Computer Vision and Pattern Recognition (CVPR), 2014
1292014
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
962017
Probabilistic Video Generation using Holistic Attribute Control
J He, AM Lehrmann, J Marino, G Mori, L Sigal
European Conference on Computer Vision (ECCV), 2018
632018
Learning Physics-guided Face Relighting under Directional Light
T Nestmeyer, JF Lalonde, I Matthews, AM Lehrmann
Computer Vision and Pattern Recognition (CVPR), 2020
512020
A Non-parametric Bayesian Network Prior of Human Pose
AM Lehrmann, PV Gehler, S Nowozin
International Conference on Computer Vision (ICCV), 2013
472013
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
192020
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
102018
Visualizing Dimensionality Reduction of Systems Biology Data
AM Lehrmann, M Huber, AC Polatkan, A Pritzkau, K Nieselt
Data Mining and Knowledge Discovery, 2013
102013
Non-parametric Structured Output Networks
AM Lehrmann, L Sigal
Advances in Neural Information Processing Systems (NeurIPS), 2017
42017
Continuous Latent Process Flows
R Deng, MA Brubaker, G Mori, A Lehrmann
Advances in Neural Information Processing Systems 34, 5162-5173, 2021
22021
Visual Reference Resolution using Attention Memory for Visual Dialog
AM Lehrmann, PH Seo
US Patent App. 15/884,339, 2019
22019
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
12021
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
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