Shengjia Zhao
Publication record assembled from the DBLP archive of ranked conferences.
Papers indexed
23
Venues
8
Active years
2016–2026
Best venue rank
A*
Where they publish
Papers
23 indexed papers, newest first.
| Year | Venue | Title | Authors |
|---|---|---|---|
| 2026 | AAAI | Multi-dimensional Neural Decoding with Orthogonal Representations for Brain-Computer Interfaces. | Kaixi Tian, Shengjia Zhao, Yuhan Zhang, Shan Yu |
| 2024 | ICRA | Online Distribution Shift Detection via Recency Prediction. | Rachel Luo, Rohan Sinha, Yixiao Sun, Ali Hindy, Shengjia Zhao, Silvio Savarese, Edward Schmerling, Marco Pavone |
| 2022 | COLT | Low-Degree Multicalibration. | Parikshit Gopalan, Michael P. Kim, Mihir Singhal, Shengjia Zhao |
| 2022 | ICLR | Comparing Distributions by Measuring Differences that Affect Decision Making. | Shengjia Zhao, Abhishek Sinha, Yutong He, Aidan Perreault, Jiaming Song, Stefano Ermon |
| 2022 | ICML | Modular Conformal Calibration. | Charles Marx, Shengjia Zhao, Willie Neiswanger, Stefano Ermon |
| 2022 | UAI | Local calibration: metrics and recalibration. | Rachel Luo, Aadyot Bhatnagar, Yu Bai, Shengjia Zhao, Huan Wang, Caiming Xiong, Silvio Savarese, Stefano Ermon, Edward Schmerling, Marco Pavone |
| 2022 | WAFR | Sample-Efficient Safety Assurances Using Conformal Prediction. | Rachel Luo, Shengjia Zhao, Jonathan Kuck, Boris Ivanovic, Silvio Savarese, Edward Schmerling, Marco Pavone |
| 2021 | AISTATS | Right Decisions from Wrong Predictions: A Mechanism Design Alternative to Individual Calibration. | Shengjia Zhao, Stefano Ermon |
| 2021 | ICLR | Improved Autoregressive Modeling with Distribution Smoothing. | Chenlin Meng, Jiaming Song, Yang Song, Shengjia Zhao, Stefano Ermon |
| 2020 | AISTATS | Permutation Invariant Graph Generation via Score-Based Generative Modeling. | Chenhao Niu, Yang Song, Jiaming Song, Shengjia Zhao, Aditya Grover, Stefano Ermon |
| 2020 | AISTATS | A Framework for Sample Efficient Interval Estimation with Control Variates. | Shengjia Zhao, Christopher Yeh, Stefano Ermon |
| 2020 | ICLR | A Theory of Usable Information under Computational Constraints. | Yilun Xu, Shengjia Zhao, Jiaming Song, Russell Stewart, Stefano Ermon |
| 2020 | ICML | Domain Adaptive Imitation Learning. | Kuno Kim, Yihong Gu, Jiaming Song, Shengjia Zhao, Stefano Ermon |
| 2020 | ICML | Individual Calibration with Randomized Forecasting. | Shengjia Zhao, Tengyu Ma, Stefano Ermon |
| 2019 | AAAI | InfoVAE: Balancing Learning and Inference in Variational Autoencoders. | Shengjia Zhao, Jiaming Song, Stefano Ermon |
| 2019 | AISTATS | Learning Controllable Fair Representations. | Jiaming Song, Pratyusha Kalluri, Aditya Grover, Shengjia Zhao, Stefano Ermon |
| 2019 | ICLR | Learning Neural PDE Solvers with Convergence Guarantees. | Jun-Ting Hsieh, Shengjia Zhao, Stephan Eismann, Lucia Mirabella, Stefano Ermon |
| 2019 | ICML | Adaptive Antithetic Sampling for Variance Reduction. | Hongyu Ren, Shengjia Zhao, Stefano Ermon |
| 2018 | ICLR | Rethinking Style and Content Disentanglement in Variational Autoencoders. | Rui Shu, Shengjia Zhao, Mykel J. Kochenderfer |
| 2018 | UAI | A Lagrangian Perspective on Latent Variable Generative Models. | Shengjia Zhao, Jiaming Song, Stefano Ermon |
| 2017 | ICLR | Generative Adversarial Learning of Markov Chains. | Jiaming Song, Shengjia Zhao, Stefano Ermon |
| 2017 | ICML | Learning Hierarchical Features from Deep Generative Models. | Shengjia Zhao, Jiaming Song, Stefano Ermon |
| 2016 | AAAI | Closing the Gap Between Short and Long XORs for Model Counting. | Shengjia Zhao, Sorathan Chaturapruek, Ashish Sabharwal, Stefano Ermon |