| Inferring Human Intent from Video by Sampling Hierarchical Plans S Holtzen, Y Zhao, T Gao, JB Tenenbaum, SC Zhu IEEE International Conference on Intelligent Robots and Systems (IROS), 2016 | 25 | 2016 |
| Classification system with methodology for efficient verification D Lisuk, S Holtzen US Patent 9,390,086, 2016 | 12 | 2016 |
| Sound Abstraction and Decomposition of Probabilistic Programs S Holtzen, G Van den Broeck, T Millstein International Conference on Machine Learning (ICML) 35, 2018 | 11 | 2018 |
| Probabilistic Program Abstractions S Holtzen, T Millstein, G Van den Broeck Uncertainty in Artificial Intelligence (UAI), 2017 | 10 | 2017 |
| Scaling exact inference for discrete probabilistic programs S Holtzen, G Van den Broeck, T Millstein Proceedings of the ACM on Programming Languages 4 (OOPSLA), 1-31, 2020 | 8 | 2020 |
| Represent and Infer Human Theory of Mind for Human-Robot Interaction Y Zhao, S Holtzen, T Gao, SC Zhu 2015 AAAI Fall Symposium Series, 2015 | 8 | 2015 |
| Symbolic Exact Inference for Discrete Probabilistic Programs S Holtzen, T Millstein, G Van den Broeck arXiv preprint arXiv:1904.02079, 2019 | 7 | 2019 |
| Generating and Sampling Orbits for Lifted Probabilistic Inference S Holtzen, T Millstein, G Van den Broeck Uncertainty in Artificial Intelligence (UAI), 2019 | 5 | 2019 |
| Dice: compiling discrete probabilistic programs for scalable inference S Holtzen, GV Broeck, T Millstein arXiv preprint arXiv:2005.09089, 2020 | 3 | 2020 |
| Factorized exact inference for discrete probabilistic programs S Holtzen, J Qian, T Millstein, G Van den Broeck Languages for Inference, 2019 | 2* | 2019 |
| On the Relationship Between Probabilistic Circuits and Determinantal Point Processes H Zhang, S Holtzen, GV Broeck Proceedings of the 36th Conference on Uncertainty in Aritifical Intelligence …, 2020 | 1 | 2020 |
| Probabilistic Program Inference With Abstractions S Holtzen, G Van den Broeck, T Millstein POPL Workshop on Probabilistic Program Semantics (PPS), 2017 | 1 | 2017 |
| Model Checking Finite-Horizon Markov Chains with Probabilistic Inference S Holtzen, S Junges, M Vazquez-Chanlatte, T Millstein, S Seshia, ... 33rd International Conference on Computer-Aided Verification (CAV), 2021 | | 2021 |
| Logical Abstractions for Noisy Variational antum Algorithm Simulation Y Huang, S Holtzen, T Millstein, G Van den Broeck, M Martonosi International Conference on Architectural Support for Programming Languages …, 2021 | | 2021 |
| 1 Probabilistic Programming S Holtzen | | |
| Logic Formulas as Program Abstractions for Quantum Circuits: A Case Study in Noisy Variational Algorithm Simulation Y Huang, S Holtzen, T Millstein, G Van den Broeck, M Martonosi | | |
| 3.3 Probabilistic Programming S Holtzen SE4ML–Software Engineering for AI-ML-based Systems, 81, 0 | | |
Guy Van den BroeckAssociate Professor and Samueli Fellow, UCLAVerified email at cs.ucla.edu
