| 2026 | CHI | "It's trained by non-disabled people": Evaluating How Image Quality Affects Product Captioning with Vision-Language Models. | Kapil Garg, Xinru Tang, Jimin Heo, Dwayne R. Morgan, Darren Gergle, Erik B. Sudderth, Anne Marie Piper |
| 2023 | UAI | A decoder suffices for query-adaptive variational inference. | Sakshi Agarwal, Gabriel Hope, Ali Younis, Erik B. Sudderth |
| 2021 | ICML | Marginalized Stochastic Natural Gradients for Black-Box Variational Inference. | Geng Ji, Debora Sujono, Erik B. Sudderth |
| 2019 | CVPR | Multi-layer Depth and Epipolar Feature Transformers for 3D Scene Reconstruction. | Daeyun Shin, Zhile Ren, Erik B. Sudderth, Charless C. Fowlkes |
| 2019 | ICCV | 3D Scene Reconstruction With Multi-Layer Depth and Epipolar Transformers. | Daeyun Shin, Zhile Ren, Erik B. Sudderth, Charless C. Fowlkes |
| 2019 | WACV | A Fusion Approach for Multi-Frame Optical Flow Estimation. | Zhile Ren, Orazio Gallo, Deqing Sun, Ming-Hsuan Yang, Erik B. Sudderth, Jan Kautz |
| 2019 | UAI | Variational Training for Large-Scale Noisy-OR Bayesian Networks. | Geng Ji, Dehua Cheng, Huazhong Ning, Changhe Yuan, Hanning Zhou, Liang Xiong, Erik B. Sudderth |
| 2018 | AISTATS | Semi-Supervised Prediction-Constrained Topic Models. | Michael C. Hughes, Gabriel Hope, Leah Weiner, Thomas H. McCoy Jr., Roy H. Perlis, Erik B. Sudderth, Finale Doshi-Velez |
| 2018 | CVPR | 3D Object Detection With Latent Support Surfaces. | Zhile Ren, Erik B. Sudderth |
| 2018 | ECCV | A Simple and Effective Fusion Approach for Multi-frame Optical Flow Estimation. | Zhile Ren, Orazio Gallo, Deqing Sun, Ming-Hsuan Yang, Erik B. Sudderth, Jan Kautz |
| 2017 | ICML | From Patches to Images: A Nonparametric Generative Model. | Geng Ji, Michael C. Hughes, Erik B. Sudderth |
| 2016 | CVPR | Three-Dimensional Object Detection and Layout Prediction Using Clouds of Oriented Gradients. | Zhile Ren, Erik B. Sudderth |
| 2015 | AISTATS | Reliable and Scalable Variational Inference for the Hierarchical Dirichlet Process. | Michael C. Hughes, Dae Il Kim, Erik B. Sudderth |
| 2015 | CVPR | Layered RGBD scene flow estimation. | Deqing Sun, Erik B. Sudderth, Hanspeter Pfister |
| 2015 | ICML | Proteins, Particles, and Pseudo-Max-Marginals: A Submodular Approach. | Jason Pacheco, Erik B. Sudderth |
| 2014 | ICML | Preserving Modes and Messages via Diverse Particle Selection. | Jason Pacheco, Silvia Zuffi, Michael J. Black, Erik B. Sudderth |
| 2014 | UAI | Nonparametric Clustering with Distance Dependent Hierarchies. | Soumya Ghosh, Michalis Raptis, Leonid Sigal, Erik B. Sudderth |
| 2013 | CVPR | A Fully-Connected Layered Model of Foreground and Background Flow. | Deqing Sun, Jonas Wulff, Erik B. Sudderth, Hanspeter Pfister, Michael J. Black |
| 2012 | CVPR | Nonparametric learning for layered segmentation of natural images. | Soumya Ghosh, Erik B. Sudderth |
| 2012 | CVPR | Nonparametric discovery of activity patterns from video collections. | Michael C. Hughes, Erik B. Sudderth |
| 2012 | CVPR | Layered segmentation and optical flow estimation over time. | Deqing Sun, Erik B. Sudderth, Michael J. Black |
| 2012 | ICML | The Nonparametric Metadata Dependent Relational Model. | Dae Il Kim, Michael C. Hughes, Erik B. Sudderth |
| 2011 | AAAI | Global Seismic Monitoring: A Bayesian Approach. | Nimar S. Arora, Stuart Russell, Paul Kidwell, Erik B. Sudderth |
| 2010 | AAAI | Automatic Inference in BLOG. | Nimar S. Arora, Stuart Russell, Erik B. Sudderth |
| 2010 | UAI | Gibbs Sampling in Open-Universe Stochastic Languages. | Nimar S. Arora, Rodrigo de Salvo Braz, Erik B. Sudderth, Stuart Russell |
| 2009 | IROS | Nonparametric belief propagation for distributed tracking of robot networks with noisy inter-distance measurements. | Jeremy Schiff, Erik B. Sudderth, Kenneth Y. Goldberg |
| 2008 | ICML | An HDP-HMM for systems with state persistence. | Emily B. Fox, Erik B. Sudderth, Michael I. Jordan, Alan S. Willsky |
| 2007 | FUSION | Hierarchical Dirichlet processes for tracking maneuvering targets. | Emily B. Fox, Erik B. Sudderth, Alan S. Willsky |
| 2007 | ICCV | Learning Multiscale Representations of Natural Scenes Using Dirichlet Processes. | Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jordan |
| 2007 | ICIP | Image Denoising with Nonparametric Hidden Markov Trees. | Jyri J. Kivinen, Erik B. Sudderth, Michael I. Jordan |
| 2006 | CVPR | Depth from Familiar Objects: A Hierarchical Model for 3D Scenes. | Erik B. Sudderth, Antonio Torralba, William T. Freeman, Alan S. Willsky |
| 2005 | ICCV | Learning Hierarchical Models of Scenes, Objects, and Parts. | Erik B. Sudderth, Antonio Torralba, William T. Freeman, Alan S. Willsky |
| 2004 | CVPR | Visual Hand Tracking Using Nonparametric Belief Propagation. | Erik B. Sudderth, Michael I. Mandel, William T. Freeman, Alan S. Willsky |
| 2003 | CVPR | Nonparametric Belief Propagation. | Erik B. Sudderth, Alexander T. Ihler, William T. Freeman, Alan S. Willsky |