Jiaming Song

SABER: Switchable and Balanced Training for Efficient LLM Reasoning AAAI 2026 Self-NPO: Data-Free Diffusion Model Enhancement via Truncated Diffusion Fine-Tuning AAAI 2026 Inductive Moment Matching ICML 2025 Decentralized Diffusion Models CVPR 2025 Score-Based Diffusion Models in Function Space JMLR 2025 Personalized Preference Fine-tuning of Diffusion Models CVPR 2025 Accelerate Multi-Agent Reinforcement Learning in Zero-Sum Games with Subgame Curriculum Learning AAAI 2024 Seer: Language Instructed Video Prediction with Latent Diffusion Models ICLR 2024 DiffiT: Diffusion Vision Transformers for Image Generation ECCV 2024 A Variational Perspective on Solving Inverse Problems with Diffusion Models ICLR 2024 Offline Imitation Learning with Suboptimal Demonstrations via Relaxed Distribution Matching AAAI 2023 Affordance Diffusion: Synthesizing Hand-Object Interactions CVPR 2023 DiffCollage: Parallel Generation of Large Content With Diffusion Models CVPR 2023 CSP: Self-Supervised Contrastive Spatial Pre-Training for Geospatial-Visual Representations ICML 2023 Loss-Guided Diffusion Models for Plug-and-Play Controllable Generation ICML 2023 Dual Diffusion Implicit Bridges for Image-to-Image Translation ICLR 2023 Pseudoinverse-Guided Diffusion Models for Inverse Problems ICLR 2023 PhysDiff: Physics-Guided Human Motion Diffusion Model ICCV 2023 SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations ICLR 2022 LISA: Learning Interpretable Skill Abstractions from Language NIPS 2022 Denoising Diffusion Restoration Models NIPS 2022 Concrete Score Matching: Generalized Score Matching for Discrete Data NIPS 2022 IS-Count: Large-Scale Object Counting from Satellite Images with Covariate-Based Importance Sampling AAAI 2022 BigDL 2.0: Seamless Scaling of AI Pipelines From Laptops to Distributed Cluster CVPR 2022 Comparing Distributions by Measuring Differences that Affect Decision Making ICLR 2022 A General Recipe for Likelihood-free Bayesian Optimization ICML 2022 Experience Replay with Likelihood-free Importance Weights L4DC 2022 D2C: Diffusion-Decoding Models for Few-Shot Conditional Generation NIPS 2021 Variational Automatic Curriculum Learning for Sparse-Reward Cooperative Multi-Agent Problems NIPS 2021 Imitation with Neural Density Models NIPS 2021 IQ-Learn: Inverse soft-Q Learning for Imitation NIPS 2021 Negative Data Augmentation ICLR 2021 Denoising Diffusion Implicit Models ICLR 2021 Improved Autoregressive Modeling with Distribution Smoothing ICLR 2021 Pseudo-Spherical Contrastive Divergence NIPS 2021 CSDI: Conditional Score-based Diffusion Models for Probabilistic Time Series Imputation NIPS 2021 Autoregressive Score Matching NIPS 2020 Training Deep Energy-Based Models with f-Divergence Minimization ICML 2020 Gaussianization Flows AISTATS 2020 Domain Adaptive Imitation Learning ICML 2020 Bridging the Gap Between f-GANs and Wasserstein GANs ICML 2020 A Theory of Usable Information under Computational Constraints ICLR 2020 Understanding the Limitations of Variational Mutual Information Estimators ICLR 2020 Robust and On-the-fly Dataset Denoising for Image Classification ECCV 2020 Permutation Invariant Graph Generation via Score-Based Generative Modeling AISTATS 2020 Multi-label Contrastive Predictive Coding NIPS 2020 Belief Propagation Neural Networks NIPS 2020 InfoVAE: Balancing Learning and Inference in Variational Autoencoders AAAI 2019 Calibrated Model-Based Deep Reinforcement Learning ICML 2019 Multi-Agent Adversarial Inverse Reinforcement Learning ICML 2019 Bias Correction of Learned Generative Models using Likelihood-Free Importance Weighting NIPS 2019 Learning Controllable Fair Representations AISTATS 2019 Multi-Agent Generative Adversarial Imitation Learning NIPS 2018 Bias and Generalization in Deep Generative Models: An Empirical Study NIPS 2018 Accelerating Natural Gradient with Higher-Order Invariance ICML 2018 Adversarial Constraint Learning for Structured Prediction IJCAI 2018 InfoGAIL: Interpretable Imitation Learning from Visual Demonstrations NIPS 2017 A-NICE-MC: Adversarial Training for MCMC NIPS 2017 Learning Hierarchical Features from Deep Generative Models ICML 2017 Factored Temporal Sigmoid Belief Networks for Sequence Learning ICML 2016