Marcus A. Brubaker

Publication Activity (10 Years)

Years Active: 2007-2024
Publications (10 Years): 62

Top Topics

Gaussian Process Latent Variable Models

Stochastic Process

Motion Synthesis

Top Venues

IEEE Trans. Pattern Anal. Mach. Intell.

Publications

Jason J. Yu, Tristan Aumentado-Armstrong, Fereshteh Forghani, Konstantinos G. Derpanis, Marcus A. Brubaker
PolyOculus: Simultaneous Multi-view Image-based Novel View Synthesis. CoRR (2024)
Shayan Shekarforoush, David B. Lindell, Marcus A. Brubaker, David J. Fleet
Improving Ab-Initio Cryo-EM Reconstruction with Semi-Amortized Pose Inference. CoRR (2024)
Jason J. Yu, Fereshteh Forghani, Konstantinos G. Derpanis, Marcus A. Brubaker
Long-Term Photometric Consistent Novel View Synthesis with Diffusion Models. ICCV (2023)
Ashkan Mirzaei, Tristan Aumentado-Armstrong, Konstantinos G. Derpanis, Jonathan Kelly, Marcus A. Brubaker, Igor Gilitschenski, Alex Levinshtein
SPIn-NeRF: Multiview Segmentation and Perceptual Inpainting with Neural Radiance Fields. CVPR (2023)
Ashkan Mirzaei, Tristan Aumentado-Armstrong, Marcus A. Brubaker, Jonathan Kelly, Alex Levinshtein, Konstantinos G. Derpanis, Igor Gilitschenski
Watch Your Steps: Local Image and Scene Editing by Text Instructions. CoRR (2023)
Shayan Shekarforoush, Amanpreet Walia, Marcus A. Brubaker, Konstantinos G. Derpanis, Alex Levinshtein
Dual-Camera Joint Deblurring-Denoising. CoRR (2023)
Ashkan Mirzaei, Tristan Aumentado-Armstrong, Marcus A. Brubaker, Jonathan Kelly, Alex Levinshtein, Konstantinos G. Derpanis, Igor Gilitschenski
Reference-guided Controllable Inpainting of Neural Radiance Fields. CoRR (2023)
Jason J. Yu, Fereshteh Forghani, Konstantinos G. Derpanis, Marcus A. Brubaker
Long-Term Photometric Consistent Novel View Synthesis with Diffusion Models. CoRR (2023)
Tristan Aumentado-Armstrong, Ashkan Mirzaei, Marcus A. Brubaker, Jonathan Kelly, Alex Levinshtein, Konstantinos G. Derpanis, Igor Gilitschenski
Reconstructive Latent-Space Neural Radiance Fields for Efficient 3D Scene Representations. CoRR (2023)
Bogdan Toader, Marcus A. Brubaker, Roy R. Lederman
Efficient high-resolution refinement in cryo-EM with stochastic gradient descent. CoRR (2023)
Ashkan Mirzaei, Tristan Aumentado-Armstrong, Marcus A. Brubaker, Jonathan Kelly, Alex Levinshtein, Konstantinos G. Derpanis, Igor Gilitschenski
Reference-guided Controllable Inpainting of Neural Radiance Fields. ICCV (2023)
Ali Maleky, Shayan Kousha, Michael S. Brown, Marcus A. Brubaker
Noise2NoiseFlow: Realistic Camera Noise Modeling without Clean Images. CVPR (2022)
Shayan Kousha, Ali Maleky, Michael S. Brown, Marcus A. Brubaker
Modeling sRGB Camera Noise with Normalizing Flows. CoRR (2022)
Shayan Shekarforoush, David B. Lindell, David J. Fleet, Marcus A. Brubaker
Residual Multiplicative Filter Networks for Multiscale Reconstruction. CoRR (2022)
Seonghyeon Nam, Marcus A. Brubaker, Michael S. Brown
Neural Image Representations for Multi-image Fusion and Layer Separation. ECCV (7) (2022)
Ali Maleky, Shayan Kousha, Michael S. Brown, Marcus A. Brubaker
Noise2NoiseFlow: Realistic Camera Noise Modeling without Clean Images. CoRR (2022)
Shayan Shekarforoush, David B. Lindell, David J. Fleet, Marcus A. Brubaker
Residual Multiplicative Filter Networks for Multiscale Reconstruction. NeurIPS (2022)
James A. Brofos, Marylou Gabrié, Marcus A. Brubaker, Roy R. Lederman
Adaptation of the Independent Metropolis-Hastings Sampler with Normalizing Flow Proposals. AISTATS (2022)
Ashkan Mirzaei, Tristan Aumentado-Armstrong, Konstantinos G. Derpanis, Jonathan Kelly, Marcus A. Brubaker, Igor Gilitschenski, Alex Levinshtein
SPIn-NeRF: Multiview Segmentation and Perceptual Inpainting with Neural Radiance Fields. CoRR (2022)
Seonghyeon Nam, Abhijith Punnappurath, Marcus A. Brubaker, Michael S. Brown
Learning sRGB-to-Raw-RGB De-rendering with Content-Aware Metadata. 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)
Shayan Kousha, Ali Maleky, Michael S. Brown, Marcus A. Brubaker
Modeling sRGB Camera Noise with Normalizing Flows. CVPR (2022)
Seonghyeon Nam, Abhijith Punnappurath, Marcus A. Brubaker, Michael S. Brown
Learning sRGB-to-Raw-RGB De-rendering with Content-Aware Metadata. CVPR (2022)
Mahmoud Afifi, Marcus A. Brubaker, Michael S. Brown
Auto White-Balance Correction for Mixed-Illuminant Scenes. WACV (2022)
Mahmoud Afifi, Marcus A. Brubaker, Michael S. Brown
HistoGAN: Controlling Colors of GAN-Generated and Real Images via Color Histograms. CVPR (2021)
Ruizhi Deng, Marcus A. Brubaker, Greg Mori, Andreas M. Lehrmann
Continuous Latent Process Flows. CoRR (2021)
Mahmoud Afifi, Marcus A. Brubaker, Michael S. Brown
Auto White-Balance Correction for Mixed-Illuminant Scenes. CoRR (2021)
Seonghyeon Nam, Marcus A. Brubaker, Michael S. Brown
Neural Image Representations for Multi-Image Fusion and Layer Separation. CoRR (2021)
Ruizhi Deng, Marcus A. Brubaker, Greg Mori, Andreas M. Lehrmann
Continuous Latent Process Flows. NeurIPS (2021)
James A. Brofos, Marcus A. Brubaker, Roy R. Lederman
Manifold Density Estimation via Generalized Dequantization. CoRR (2021)
Mahmoud Afifi, Abdullah Abuolaim, Mostafa Hussien, Marcus A. Brubaker, Michael S. Brown
CAMS: Color-Aware Multi-Style Transfer. CoRR (2021)
Ivan Kobyzev, Simon J. D. Prince, Marcus A. Brubaker
Normalizing Flows: An Introduction and Review of Current Methods. IEEE Trans. Pattern Anal. Mach. Intell. 43 (11) (2021)
Shayan Kousha, Marcus A. Brubaker
Zero-shot Learning with Class Description Regularization. CoRR (2021)
Jason J. Yu, Konstantinos G. Derpanis, Marcus A. Brubaker
Wavelet Flow: Fast Training of High Resolution Normalizing Flows. NeurIPS (2020)
Ruizhi Deng, Yanshuai Cao, Bo Chang, Leonid Sigal, Greg Mori, Marcus A. Brubaker
Variational Hyper RNN for Sequence Modeling. CoRR (2020)
Mahmoud Afifi, Marcus A. Brubaker, Michael S. Brown
HistoGAN: Controlling Colors of GAN-Generated and Real Images via Color Histograms. CoRR (2020)
Saeed Ghorbani, Calden Wloka, Ali Etemad, Marcus A. Brubaker, Nikolaus F. Troje
Probabilistic Character Motion Synthesis using a Hierarchical Deep Latent Variable Model. Comput. Graph. Forum 39 (8) (2020)
Jason J. Yu, Konstantinos G. Derpanis, Marcus A. Brubaker
Wavelet Flow: Fast Training of High Resolution Normalizing Flows. CoRR (2020)
Ruizhi Deng, Bo Chang, Marcus A. Brubaker, Greg Mori, Andreas M. Lehrmann
Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows. CoRR (2020)
Saeed Ghorbani, Calden Wloka, Ali Etemad, Marcus A. Brubaker, Nikolaus F. Troje
Probabilistic Character Motion Synthesis using a Hierarchical Deep Latent Variable Model. CoRR (2020)
Ruizhi Deng, Bo Chang, Marcus A. Brubaker, Greg Mori, Andreas M. Lehrmann
Modeling Continuous Stochastic Processes with Dynamic Normalizing Flows. NeurIPS (2020)
Karen Ullrich, Rianne van den Berg, Marcus A. Brubaker, David J. Fleet, Max Welling
Differentiable probabilistic models of scientific imaging with the Fourier slice theorem. CoRR (2019)
Yash Sharma, Gavin Weiguang Ding, Marcus A. Brubaker
On the Effectiveness of Low Frequency Perturbations. IJCAI (2019)
Abdelrahman Abdelhamed, Marcus A. Brubaker, Michael S. Brown
Noise Flow: Noise Modeling with Conditional Normalizing Flows. CoRR (2019)
Yash Sharma, Gavin Weiguang Ding, Marcus A. Brubaker
On the Effectiveness of Low Frequency Perturbations. CoRR (2019)
Karen Ullrich, Rianne van den Berg, Marcus A. Brubaker, David J. Fleet, Max Welling
Differentiable Probabilistic Models of Scientific Imaging with the Fourier Slice Theorem. UAI (2019)
Ivan Kobyzev, Simon Prince, Marcus A. Brubaker
Normalizing Flows: Introduction and Ideas. CoRR (2019)
Micha Livne, Leonid Sigal, Marcus A. Brubaker, David J. Fleet
Walking on Thin Air: Environment-Free Physics-Based Markerless Motion Capture. CRV (2018)
Matthew Tesfaldet, Marcus A. Brubaker, Konstantinos G. Derpanis
Two-Stream Convolutional Networks for Dynamic Texture Synthesis. CVPR (2018)
Micha Livne, Leonid Sigal, Marcus A. Brubaker, David J. Fleet
Walking on Thin Air: Environment-Free Physics-based Markerless Motion Capture. CoRR (2018)
Matthew Tesfaldet, Nariman Saftarli, Marcus A. Brubaker, Konstantinos G. Derpanis
Convolutional Photomosaic Generation via Multi-scale Perceptual Losses. ECCV Workshops (3) (2018)
Zhihao Luo, Marcus A. Brubaker, Michael Brudno
Size and Texture-Based Classification of Lung Tumors with 3D CNNs. WACV (2017)
Ali Punjani, Marcus A. Brubaker, David J. Fleet
Building Proteins in a Day: Efficient 3D Molecular Structure Estimation with Electron Cryomicroscopy. IEEE Trans. Pattern Anal. Mach. Intell. 39 (4) (2017)
Matthew Tesfaldet, Marcus A. Brubaker, Konstantinos G. Derpanis
Two-Stream Convolutional Networks for Dynamic Texture Synthesis. CoRR (2017)
Wei-Chiu Ma, Shenlong Wang, Marcus A. Brubaker, Sanja Fidler, Raquel Urtasun
Find your way by observing the sun and other semantic cues. ICRA (2017)
Yali Wang, Marcus A. Brubaker, Brahim Chaib-draa, Raquel Urtasun
Sequential Inference for Deep Gaussian Process. AISTATS (2016)
Wei-Chiu Ma, Shenlong Wang, Marcus A. Brubaker, Sanja Fidler, Raquel Urtasun
Find your Way by Observing the Sun and Other Semantic Cues. CoRR (2016)
Marcus A. Brubaker, Andreas Geiger, Raquel Urtasun
Map-Based Probabilistic Visual Self-Localization. IEEE Trans. Pattern Anal. Mach. Intell. 38 (4) (2016)
Marcus A. Brubaker, Ali Punjani, David J. Fleet
Building Proteins in a Day: Efficient 3D Molecular Reconstruction. CoRR (2015)
Marcus A. Brubaker, Ali Punjani, David J. Fleet
Building proteins in a day: Efficient 3D molecular reconstruction. CVPR (2015)
Yanshuai Cao, Marcus A. Brubaker, David J. Fleet, Aaron Hertzmann
Efficient Optimization for Sparse Gaussian Process Regression. IEEE Trans. Pattern Anal. Mach. Intell. 37 (12) (2015)
Ali Punjani, Marcus A. Brubaker
Microscopic Advances with Large-Scale Learning: Stochastic Optimization for Cryo-EM. CoRR (2015)
Yali Wang, Marcus A. Brubaker, Brahim Chaib-draa, Raquel Urtasun
Bayesian Filtering with Online Gaussian Process Latent Variable Models. UAI (2014)
Yanshuai Cao, Marcus A. Brubaker, David J. Fleet, Aaron Hertzmann
Efficient Optimization for Sparse Gaussian Process Regression. CoRR (2013)
Marcus A. Brubaker, Andreas Geiger, Raquel Urtasun
Lost! Leveraging the Crowd for Probabilistic Visual Self-Localization. CVPR (2013)
Yanshuai Cao, Marcus A. Brubaker, David J. Fleet, Aaron Hertzmann
Efficient Optimization for Sparse Gaussian Process Regression. NIPS (2013)
Marcus A. Brubaker, Mathieu Salzmann, Raquel Urtasun
A Family of MCMC Methods on Implicitly Defined Manifolds. AISTATS (2012)
Marcus A. Brubaker, David J. Fleet, Aaron Hertzmann
Physics-Based Person Tracking Using the Anthropomorphic Walker. Int. J. Comput. Vis. 87 (1-2) (2010)
Navdeep Jaitly, Marcus A. Brubaker, John L. Rubinstein, Ryan H. Lilien
A Bayesian method for 3D macromolecular structure inference using class average images from single particle electron microscopy. Bioinform. 26 (19) (2010)
Marcus A. Brubaker, Leonid Sigal, David J. Fleet
Estimating contact dynamics. ICCV (2009)
Marcus A. Brubaker, David J. Fleet
The Kneed Walker for human pose tracking. CVPR (2008)
Marcus A. Brubaker, David J. Fleet, Aaron Hertzmann
Physics-Based Person Tracking Using Simplified Lower-Body Dynamics. CVPR (2007)