← Authors

Nicholas Ruozzi

24 papers · 2012–2026 · 9 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (16) 🧭 Keyword Pioneer 🌍 Conference Polyglot (9) πŸƒ Academic Marathon (13) 🐝 Cross-Pollinator (15) 🌈 Renaissance Researcher (7) 🐺 Lone Wolf (3) πŸ† Keyword Champion πŸ”₯ Unstoppable (7) πŸš€ Conference Pioneer πŸ“ˆ Trend Setter πŸ’Ž Century Club (23) πŸ—ƒοΈ Keyword Collector (99)

Conferences

AISTATS (6) NIPS (6) IJCAI (4) AAAI (2) UAI (2) ICCV (1) ICML (1) JMLR (1) RSS (1)

Top co-authors

Vibhav Gogate (6) Hailiang Dong (4) Hao Xiong (4) Yuqiao Chen (3) Sriraam Natarajan (3) Tony Jebara (3) James Amato (3) Chiradeep Roy (2) Tahrima Rahman (2) Yu Xiang (2)

Keywords

graphical model (8) variational inference (6) markov random field (5) partition function (5) belief propagation (5) approximate inference (4) structured prediction (3) lifted inference (3) probabilistic inference (3) graph cover (2) markov logic network (2) maximum likelihood estimation (2) cutset network (2) neural network (2) message passing (2) map inference (2) bethe approximation (2) probabilistic graphical model (2) video segmentation (1) density estimation (1)

Papers

A Novel Approach to Evaluating Evaluation Metrics for Multi-Output Structured Prediction AAAI 2026
CMB-ML: A Cosmic Microwave Background Dataset for the Oldest Possible Computer Vision Task ICCV 2025
CaptainCook4D: A Dataset for Understanding Errors in Procedural Activities NIPS 2024
Learning Distributionally Robust Tractable Probabilistic Models in Continuous Domains UAI 2024
A New Modeling Framework for Continuous, Sequential Domains AISTATS 2023
Self-Supervised Unseen Object Instance Segmentation via Long-Term Robot Interaction RSS 2023
Boosting the Performance of Generic Deep Neural Network Frameworks with Log-supermodular CRFs NIPS 2022
Conditionally Tractable Density Estimation using Neural Networks AISTATS 2022
Relational Neural Markov Random Fields AISTATS 2022
Dynamic Cutset Networks AISTATS 2021
General Purpose MRF Learning with Neural Network Potentials IJCAI 2020
Lifted Hybrid Variational Inference IJCAI 2020
Marginal Inference in Continuous Markov Random Fields Using Mixtures AAAI 2019
Correlated Variational Auto-Encoders ICML 2019
Lifted Message Passing for Hybrid Probabilistic Inference IJCAI 2019
One-Shot Marginal MAP Inference in Markov Random Fields UAI 2019
Sparse Approximate Conic Hulls NIPS 2017
Efficient Inference for Untied MLNs IJCAI 2017
A Lower Bound on the Partition Function of Attractive Graphical Models in the Continuous Case AISTATS 2017
Bethe Learning of Graphical Models via MAP Decoding AISTATS 2016
Exactness of Approximate MAP Inference in Continuous MRFs NIPS 2015
Making Pairwise Binary Graphical Models Attractive NIPS 2014
Message-Passing Algorithms for Quadratic Minimization JMLR 2013
The Bethe Partition Function of Log-supermodular Graphical Models NIPS 2012