2021

1. [37]

   Jiaming Song, Chenlin Meng, Stefano Ermon Denoising Diffusion Implicit Models ICLR 2021, In International Conference on Learning Representations. [code]
2. [36]

   Abhishek Sinha*, Ayush Kumar*, Jiaming Song*, Burak Ukzent, Hongxia Jin, Stefano Ermon Negative Data Augmentation ICLR 2021, In International Conference on Learning Representations.
3. [35]

   Chenlin Meng, Jiaming Song, Yang Song, Shengjia Zhao, Stefano Ermon Improved Autoregressive Modeling with Distribution Smoothing ICLR 2021, In International Conference on Learning Representations, (Oral presentation).

2020

1. [34]

   Jiaming Song, Stefano Ermon Multi-label Contrastive Predictive Coding NeurIPS 2020, In Neural Information Processing Systems, (Oral presentation).
2. [33]

   Chenlin Meng, Lantao Yu, Yang Song, Jiaming Song, Stefano Ermon Autoregressive Score Matching NeurIPS 2020, In Neural Information Processing Systems.
3. [32]

   Jonathan Kuck, Shuvam Chakraborty, Hao Tang, Rachel Luo, Jiaming Song, Ashish Sabharwal, Stefano Ermon Belief Propagation Neural Networks NeurIPS 2020, In Neural Information Processing Systems.
4. [31]

   Jiaming Song, Michael Auli, Yann Dauphin, Tengyu Ma Robust and On-the-fly Dataset Denoising for Image Classification ECCV 2020, In European Conference on Computer Vision. [slides]
5. [30]

   Chenhao Niu, Yang Song, Jiaming Song, Shengjia Zhao, Aditya Grover, Stefano Ermon Permutation Invariant Graph Generation via Score-Based Generative Modeling AISTATS 2020, In International Conference on Artificial Intelligence and Statistics. [code]
6. [29]

   Chenlin Meng, Yang Song, Jiaming Song, Stefano Ermon Gaussianization Flows AISTATS 2020, In International Conference on Artificial Intelligence and Statistics. [code]
7. [28]

   Lantao Yu, Yang Song, Jiaming Song, Stefano Ermon Training Deep Energy-Based Models with f-Divergence Minimization ICML 2020, In International Conference on Machine Learning.
8. [27]

   Jiaming Song, Stefano Ermon Bridging the Gap Between f-GANs and Wasserstein GANs ICML 2020, In International Conference on Machine Learning. [slides] [code]
9. [26]

   Kuno Kim, Yihong Gu, Jiaming Song, Shengjia Zhao, Stefano Ermon Domain Adaptive Imitation Learning ICML 2020, In International Conference on Machine Learning.
10. [25]

    Jiaming Song, Stefano Ermon Understanding the Limitations of Variational Mutual Information Estimators ICLR 2020, In International Conference on Learning Representations. [slides] [code]
11. [24]

    Yilun Xu, Shengjia Zhao, Jiaming Song, Russell Stewart, Stefano Ermon A Theory of Usable Information under Computational Constraints ICLR 2020, In International Conference on Learning Representations, (Oral presentation).
12. [23]

    Nate Gruver, Jiaming Song, Mykel J Kochenderfer, Stefano Ermon Multi-agent Adversarial Inverse Reinforcement Learning with Latent Variables AAMAS 2020, In International Conference on Autonomous Agents and MultiAgent Systems (extended abstract).
13. [22]

    Kuno Kim, Akshat Jindal, Yang Song, Jiaming Song, Yanan Sui, Stefano Ermon Imitation with Neural Density Models Preprint, arXiv:2010.09808.
14. [21]

    Rachel Luo, Shengjia Zhao, Jiaming Song, Jonathan Kuck, Stefano Ermon, Silvio Savarese Privacy Preserving Recalibration under Domain Shift Preprint, arXiv:2008.09643.
15. [20]

    Samarth Sinha*, Jiaming Song*, Animesh Garg, Stefano Ermon Experience Replay with Likelihood-free Importance Weights Preprint, arXiv:2006.13169.

2019

1. [19]

   Aditya Grover, Jiaming Song, Ashish Kapoor, Kenneth Tran, Alekh Agarwal, Eric J Horvitz, Stefano Ermon Bias Correction of Learned Generative Models using Likelihood-free Importance Weighting NeurIPS 2019, In Advances in Neural Information Processing Systems.
2. [18]

   Ali Malik, Volodymyr Kuleshov, Jiaming Song, Danny Nemer, Harlan Seymour, Stefano Ermon Calibrated Model-based Deep Reinforcement Learning ICML 2019, In International Conference on Machine Learning. [code]
3. [17]

   Lantao Yu, Jiaming Song, Stefano Ermon Multi-agent Adversarial Inverse Reinforcement Learning ICML 2019, In International Conference on Machine Learning. [code]
4. [16]

   Shengjia Zhao, Jiaming Song, Stefano Ermon InfoVAE: Balancing Learning and Inference in Variational Autoencoders AAAI 2019, In AAAI Conference on Artificial Intelligence.
5. [15]

   Jiaming Song, Pratyusha Kalluri, Aditya Grover, Shengjia Zhao, Stefano Ermon Learning Controllable Fair Representations AISTATS 2019, In International Conference on Artificial Intelligence and Statistics. [code]
6. [14]

   Jiaming Song, Yang Song, Stefano Ermon Unsupervised Out-of-Distribution Detection with Batch Normalization Preprint, arXiv:1910.09115.

2018

1. [13]

   Jiaming Song, Hongyu Ren, Dorsa Sadigh, Stefano Ermon Multi-Agent Generative Adversarial Imitation Learning NeurIPS 2018, In Advances in Neural Information Processing Systems. [code]
2. [12]

   Shengjia Zhao, Hongyu Ren, Arianna Yuan, Jiaming Song, Noah Goodman, Stefano Ermon Bias and Generalization in Deep Generative Models: An Empirical Study NeurIPS 2018, In Advances in Neural Information Processing Systems, (Spotlight presentation). [code]
3. [11]

   Shengjia Zhao, Jiaming Song, Stefano Ermon The Information Autoencoding Family: A Lagrangian Perspective on Latent Variable Generative Models UAI 2018, In Conference on Uncertainty in Artificial Intelligence, (Oral presentation). [code]
4. [10]

   Yang Song, Jiaming Song, Stefano Ermon Accelerating Natural Gradient with Higher-Order Invariance ICML 2018, In International Conference on Machine Learning. [code]
5. [9]

   Hongyu Ren, Russell Stewart, Jiaming Song, Volodymyr Kuleshov, Stefano Ermon Adversarial Constraint Learning for Structured Prediction IJCAI 2018, In International Joint Conference on Artificial Intelligence. [code]
6. [8]

   Hongyu Ren, Russell Stewart, Jiaming Song, Volodymyr Kuleshov, Stefano Ermon Learning with weak supervision from physics and data-driven constraints AI Magazine, AI Magazine.

2017

1. [7]

   Jiaming Song, Shengjia Zhao, Stefano Ermon A-NICE-MC: Adversarial training for MCMC NeurIPS 2017, In Advances in Neural Information Processing Systems. [slides] [code] [blog]
2. [5]

   Yunzhu Li, Jiaming Song, Stefano Ermon InfoGAIL: Interpretable imitation learning from visual demonstrations NeurIPS 2017, In Advances in Neural Information Processing Systems. [code]
3. [6]

   Shengjia Zhao, Jiaming Song, Stefano Ermon Learning Hierarchical Features from Deep Generative Models ICML 2017, In International Conference on Machine Learning. [code]
4. [4]

   Shengjia Zhao, Jiaming Song, Stefano Ermon Towards deeper understanding of variational autoencoding models Preprint, arXiv:1702.08658.

2016

1. [3]

   Jiaming Song, Zhe Gan, Lawrence Carin Factored Temporal Sigmoid Belief Networks for Sequence Learning ICML 2016, In International Conference on Machine Learning.
2. [2]

   Bei Chen, Ning Chen, Jun Zhu, Jiaming Song, Bo Zhang Discriminative nonparametric latent feature relational models with data augmentation AAAI 2016, In AAAI Conference on Artificial Intelligence.
3. [1]

   Jun Zhu, Jiaming Song, Bei Chen Max-margin Nonparametric Latent Feature Models for Link Prediction Preprint, arXiv:1602.07428.