Publications
2022
- [54]eDiff-I: Text-to-Image Diffusion Models with Ensemble of Expert Denoisers
Preprint, arXiv preprint arXiv:2211.01324.[website] - [53]JPEG Artifact Correction using Denoising Diffusion Restoration Models
NeurIPS 2022 SBM Workshop, In Neural Information Processing Systems (NeurIPS) Workshop on Score-Based Methods.[website] [code] - [52]Denoising Diffusion Restoration Models
NeurIPS 2022, In Neural Information Processing Systems.[website] [code] Short version in ICLR 2022 Workshop on Deep Generative Models for Highly Structured Data (Oral presentation). - [51]Concrete Score Matching: Generalized Score Matching for Discrete Data
NeurIPS 2022, In Neural Information Processing Systems. - [50]LISA: Learning Interpretable Skill Abstractions from Language
NeurIPS 2022, In Neural Information Processing Systems. - [49]A General Recipe for Likelihood-free Bayesian Optimization
ICML 2022, In International Conference on Machine Learning, Long oral presentation (Top 2.2%).[website] [code] - [48]Experience Replay with Likelihood-free Importance Weights
L4DC 2022, In 4th Annual Conference on Learning for Dynamics and Control, Best paper award finalist. - [47]SDEdit: Image Synthesis and Editing with Stochastic Differential Equations
ICLR 2022, In International Conference on Learning Representations.[website] [code] [colab] - [46]Comparing Distributions by Measuring Differences that Affect Decision Making
ICLR 2022, In International Conference on Learning Representations, ICLR 2022 Outstanding Paper Award. - [45]IS-COUNT: Large-scale Object Counting from Satellite Images with Covariate-based Importance Sampling
AAAI 2022, In AAAI Conference on Artificial Intelligence.[website] [code] [colab] - [44]Beyond the Imitation Game: Quantifying and Extrapolating the Capabilities of Language Models
Preprint, arXiv preprint arXiv:2206.04615.
2021
- [41]D2C: Diffusion-Denoising Models for Few-shot Conditional Generation
NeurIPS 2021, In Neural Information Processing Systems.[website] [code] [colab] - [40]IQ-Learn: Inverse soft-Q Learning for Imitation
NeurIPS 2021, In Neural Information Processing Systems, Spotlight presentation.[website] [code] - [39]Pseudo-Spherical Contrastive Divergence
NeurIPS 2021, In Neural Information Processing Systems. - [38]CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation
NeurIPS 2021, In Neural Information Processing Systems.[code] - [37]Variational Automatic Curriculum Learning for Sparse-Reward Cooperative Multi-Agent Problems
NeurIPS 2021, In Neural Information Processing Systems.[website] [code] - [36]Imitation with Neural Density Models
NeurIPS 2021, In Neural Information Processing Systems. - [35]Denoising Diffusion Implicit Models
ICLR 2021, In International Conference on Learning Representations.[code] - [34]Negative Data Augmentation
ICLR 2021, In International Conference on Learning Representations.[code] - [33]Improved Autoregressive Modeling with Distribution Smoothing
ICLR 2021, In International Conference on Learning Representations, Oral presentation.[code]
2020
- [32]Multi-label Contrastive Predictive Coding
NeurIPS 2020, In Neural Information Processing Systems, Oral presentation. - [31]Autoregressive Score Matching
NeurIPS 2020, In Neural Information Processing Systems. - [30]Belief Propagation Neural Networks
NeurIPS 2020, In Neural Information Processing Systems. - [29]Robust and On-the-fly Dataset Denoising for Image Classification
ECCV 2020, In European Conference on Computer Vision.[slides] - [28]Permutation Invariant Graph Generation via Score-Based Generative Modeling
AISTATS 2020, In International Conference on Artificial Intelligence and Statistics.[code] - [27]Gaussianization Flows
AISTATS 2020, In International Conference on Artificial Intelligence and Statistics.[code] - [26]Training Deep Energy-Based Models with f-Divergence Minimization
ICML 2020, In International Conference on Machine Learning. - [25]Bridging the Gap Between f-GANs and Wasserstein GANs
ICML 2020, In International Conference on Machine Learning.[slides] [code] - [24]Domain Adaptive Imitation Learning
ICML 2020, In International Conference on Machine Learning. - [23]Understanding the Limitations of Variational Mutual Information Estimators
ICLR 2020, In International Conference on Learning Representations.[slides] [code] - [22]A Theory of Usable Information under Computational Constraints
ICLR 2020, In International Conference on Learning Representations, Oral presentation. - [21]Multi-agent Adversarial Inverse Reinforcement Learning with Latent Variables
AAMAS 2020, In International Conference on Autonomous Agents and MultiAgent Systems (extended abstract). - [20]Privacy Preserving Recalibration under Domain Shift
Preprint, arXiv:2008.09643.
2019
- [19]Bias Correction of Learned Generative Models using Likelihood-free Importance Weighting
NeurIPS 2019, In Advances in Neural Information Processing Systems. - [18]Calibrated Model-based Deep Reinforcement Learning
ICML 2019, In International Conference on Machine Learning.[code] - [17]Multi-agent Adversarial Inverse Reinforcement Learning
ICML 2019, In International Conference on Machine Learning.[code] - [16]InfoVAE: Balancing Learning and Inference in Variational Autoencoders
AAAI 2019, In AAAI Conference on Artificial Intelligence. - [15]Learning Controllable Fair Representations
AISTATS 2019, In International Conference on Artificial Intelligence and Statistics.[code] - [14]Unsupervised Out-of-Distribution Detection with Batch Normalization
Preprint, arXiv:1910.09115.
2018
- [13]Multi-Agent Generative Adversarial Imitation Learning
NeurIPS 2018, In Advances in Neural Information Processing Systems.[code] - [12]Bias and Generalization in Deep Generative Models: An Empirical Study
NeurIPS 2018, In Advances in Neural Information Processing Systems, Spotlight presentation.[code] - [11]The Information Autoencoding Family: A Lagrangian Perspective on Latent Variable Generative Models
UAI 2018, In Conference on Uncertainty in Artificial Intelligence, Oral presentation.[code] - [10]Accelerating Natural Gradient with Higher-Order Invariance
ICML 2018, In International Conference on Machine Learning.[code] - [9]Adversarial Constraint Learning for Structured Prediction
IJCAI 2018, In International Joint Conference on Artificial Intelligence.[code] - [8]Learning with weak supervision from physics and data-driven constraints
AI Magazine, AI Magazine.
2017
- [7]A-NICE-MC: Adversarial training for MCMC
NeurIPS 2017, In Advances in Neural Information Processing Systems.[slides] [code] [blog] - [5]InfoGAIL: Interpretable imitation learning from visual demonstrations
NeurIPS 2017, In Advances in Neural Information Processing Systems.[code] - [6]Learning Hierarchical Features from Deep Generative Models
ICML 2017, In International Conference on Machine Learning.[code] - [4]Towards deeper understanding of variational autoencoding models
Preprint, arXiv:1702.08658.
2016
- [3]Factored Temporal Sigmoid Belief Networks for Sequence Learning
ICML 2016, In International Conference on Machine Learning. - [2]Discriminative nonparametric latent feature relational models with data augmentation
AAAI 2016, In AAAI Conference on Artificial Intelligence. - [1]Max-margin Nonparametric Latent Feature Models for Link Prediction
Preprint, arXiv:1602.07428.