Query-Based Outlier Detection in Heterogeneous Information Networks. - Jonathan Kuck; Honglei Zhuang; Xifeng Yan; Hasan Cam; Jiawei Han 001 (EDBT, 2015)

Approximate Inference via Weighted Rademacher Complexity. - Jonathan Kuck; Ashish Sabharwal; Stefano Ermon (AAAI, 2018)

Approximating the Permanent by Sampling from Adaptive Partitions. - Jonathan Kuck; Tri Dao; Hamid Rezatofighi; Ashish Sabharwal; Stefano Ermon (NeurIPS, 2019)

Adaptive Hashing for Model Counting. - Jonathan Kuck; Tri Dao; Shenjia Zhao; Burak Bartan; Ashish Sabharwal; Stefano Ermon (UAI, 2019)

Belief Propagation Neural Networks. - Jonathan Kuck; Shuvam Chakraborty; Hao Tang 008; Rachel Luo; Jiaming Song; Ashish Sabharwal; Stefano Ermon (NeurIPS, 2020)

Privacy Preserving Recalibration under Domain Shift. - Rachel Luo; Shengjia Zhao; Jiaming Song; Jonathan Kuck; Stefano Ermon; Silvio Savarese (CoRR, 2020)

Fast approximate inference: shifting the Pareto frontier via adaptation. - Jonathan Kuck (2020)

Equivariant Neural Network for Factor Graphs. - Fan-Yun Sun; Jonathan Kuck; Hao Tang 008; Stefano Ermon (CoRR, 2021)

Diagnostic Runtime Monitoring with Martingales. - Ali Hindy; Rachel Luo; Somrita Banerjee; Jonathan Kuck; Edward Schmerling; Marco Pavone 001 (CoRR, 2024)

Sample-efficient safety assurances using conformal prediction. - Rachel Luo; Shengjia Zhao; Jonathan Kuck; Boris Ivanovic; Silvio Savarese; Edward Schmerling; Marco Pavone 001 (Int. J. Robotics Res., 2024)