| 2026 | AAAI | The Limitations and Power of NP-Oracle Based Functional Synthesis Techniques. | Brendan Juba, Kuldeep S. Meel |
| 2026 | COLT | Stochastic Safe Action Model Learning. | Zihao Deng, Brendan Juba |
| 2025 | ICLR | Distribution-Specific Agnostic Conditional Classification With Halfspaces. | Jizhou Huang, Brendan Juba |
| 2025 | IJCAI | Polynomial-Time Relational Probabilistic Inference in Open Universes. | Luise Ge, Brendan Juba, Kris Nilsson |
| 2024 | AAAI | Learning Safe Action Models with Partial Observability. | Hai S. Le, Brendan Juba, Roni Stern |
| 2024 | AAAI | An Approximate Skolem Function Counter. | Arijit Shaw, Brendan Juba, Kuldeep S. Meel |
| 2024 | ICAPS | Safe Learning of PDDL Domains with Conditional Effects. | Argaman Mordoch, Enrico Scala, Roni Stern, Brendan Juba |
| 2024 | IJCAI | The Impact of Features Used by Algorithms on Perceptions of Fairness. | Andrew Estornell, Tina Zhang, Sanmay Das, Chien-Ju Ho, Brendan Juba, Yevgeniy Vorobeychik |
| 2023 | AAAI | Popularizing Fairness: Group Fairness and Individual Welfare. | Andrew Estornell, Sanmay Das, Brendan Juba, Yevgeniy Vorobeychik |
| 2023 | AAAI | Learning Safe Numeric Action Models. | Argaman Mordoch, Brendan Juba, Roni Stern |
| 2022 | AAAI | Learning Probably Approximately Complete and Safe Action Models for Stochastic Worlds. | Brendan Juba, Roni Stern |
| 2022 | AISTATS | Polynomial Time Reinforcement Learning in Factored State MDPs with Linear Value Functions. | Zihao Deng, Siddartha Devic, Brendan Juba |
| 2022 | AISTATS | Conditional Linear Regression for Heterogeneous Covariances. | Leda Liang, Brendan Juba |
| 2022 | CAV | A Scalable Shannon Entropy Estimator. | Priyanka Golia, Brendan Juba, Kuldeep S. Meel |
| 2022 | COLT | Hardness of Maximum Likelihood Learning of DPPs. | Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie |
| 2021 | AISTATS | List Learning with Attribute Noise. | Mahdi Cheraghchi, Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie |
| 2021 | ICLR | One Network Fits All? Modular versus Monolithic Task Formulations in Neural Networks. | Atish Agarwala, Abhimanyu Das, Brendan Juba, Rina Panigrahy, Vatsal Sharan, Xin Wang, Qiuyi Zhang |
| 2021 | ICML | Probabilistic Generating Circuits. | Honghua Zhang, Brendan Juba, Guy Van den Broeck |
| 2021 | IJCAI | Learning Implicitly with Noisy Data in Linear Arithmetic. | Alexander Philipp Rader, Ionela G. Mocanu, Vaishak Belle, Brendan Juba |
| 2021 | KR | Safe Learning of Lifted Action Models. | Brendan Juba, Hai S. Le, Roni Stern |
| 2020 | AAAI | More Accurate Learning of k-DNF Reference Classes. | Brendan Juba, Hengxuan Li |
| 2020 | AISTATS | Conditional Linear Regression. | Diego Calderon, Brendan Juba, Sirui Li, Zongyi Li, Lisa Ruan |
| 2020 | ECAI | Polynomial-Time Implicit Learnability in SMT. | Ionela G. Mocanu, Vaishak Belle, Brendan Juba |
| 2020 | IGARSS | A Tensor Decomposition Method for Unsupervised Feature Learning on Satellite Imagery. | Golnoosh Dehghanpoor, Michael D. Frachetti, Brendan Juba |
| 2019 | AAAI | Polynomial-Time Probabilistic Reasoning with Partial Observations via Implicit Learning in Probability Logics. | Brendan Juba |
| 2019 | AAAI | Precision-Recall versus Accuracy and the Role of Large Data Sets. | Brendan Juba, Hai S. Le |
| 2019 | AAAI | Safe Partial Diagnosis from Normal Observations. | Roni Stern, Brendan Juba |
| 2019 | AISTATS | Conditional Sparse $L_p$-norm Regression With Optimal Probability. | John Hainline, Brendan Juba, Hai S. Le, David P. Woodruff |
| 2019 | ALT | Hardness of Improper One-Sided Learning of Conjunctions For All Uniformly Falsifiable CSPs. | Alexander Durgin, Brendan Juba |
| 2018 | AAAI | Conditional Linear Regression. | Diego Calderon, Brendan Juba, Zongyi Li, Lisa Ruan |
| 2018 | AAAI | Learning Abduction Using Partial Observability. | Brendan Juba, Zongyi Li, Evan Miller |
| 2018 | AAAI | Learning Abduction Under Partial Observability. | Brendan Juba, Zongyi Li, Evan Miller |
| 2018 | WACV | Anomaly Explanation Using Metadata. | Di Qi, Joshua Arfin, Mengxue Zhang, Tushar Mathew, Robert Pless, Brendan Juba |
| 2017 | IJCAI | Coordinated Versus Decentralized Exploration In Multi-Agent Multi-Armed Bandits. | Mithun Chakraborty, Kai Yee Phoebe Chua, Sanmay Das, Brendan Juba |
| 2017 | IJCAI | Efficient, Safe, and Probably Approximately Complete Learning of Action Models. | Roni Stern, Brendan Juba |
| 2016 | AAAI | Learning Abductive Reasoning Using Random Examples. | Brendan Juba |
| 2016 | ICALP | AC^0 o MOD_2 Lower Bounds for the Boolean Inner Product. | Mahdi Cheraghchi, Elena Grigorescu, Brendan Juba, Karl Wimmer, Ning Xie |
| 2015 | NDSS | Principled Sampling for Anomaly Detection. | Brendan Juba, Christopher Musco, Fan Long, Stelios Sidiroglou-Douskos, Martin C. Rinard |
| 2013 | IJCAI | Implicit Learning of Common Sense for Reasoning. | Brendan Juba |
| 2013 | PERCOM | Compatibility among diversity Foundations, lessons, and directions of semantic communication. | Brendan Juba |
| 2011 | ALT | Semantic Communication for Simple Goals Is Equivalent to On-line Learning. | Brendan Juba, Santosh S. Vempala |
| 2011 | PODC | A theory of goal-oriented communication. | Oded Goldreich, Brendan Juba, Madhu Sudan |
| 2011 | PODC | Reliable end-user communication under a changing packet network protocol. | Brendan Juba |
| 2008 | STOC | Universal semantic communication I. | Brendan Juba, Madhu Sudan |
| 2006 | ICML | Estimating relatedness via data compression. | Brendan Juba |