← Authors

Jiaming Song

60 papers · 2016–2026 · 11 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (9) 🌍 Conference Polyglot (11) πŸƒ Academic Marathon (9) 🌈 Renaissance Researcher (9) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (17) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird 🌟 Keyword Trendsetter Combo (4) πŸ† Grand Slam πŸ‘‘ Triple Crown 🀝 Dynamic Duo (43) πŸ”¬ Deep Specialist (12) πŸ’Ž Century Club (58) πŸš€ Conference Pioneer ⚑ Prolific Year (9) πŸ“ˆ Trend Setter πŸ—ƒοΈ Keyword Collector (220) πŸ”₯ Unstoppable (10)

Conferences

NIPS (17) ICML (12) ICLR (11) AAAI (6) CVPR (5) AISTATS (3) ECCV (2) ICCV (1) IJCAI (1) JMLR (1) L4DC (1)

Top co-authors

Stefano Ermon (43) Yang Song (10) Shengjia Zhao (10) Chenlin Meng (9) Lantao Yu (6) Arash Vahdat (6) Jan Kautz (6) Aditya Grover (3) Kuno Kim (3) Yutong He (3)

Research topics

Reinforcement Learning (1)

Keywords

diffusion model (9) generative model (8) imitation learning (6) density estimation (5) variational inference (4) importance sampling (4) representation learning (4) image generation (4) density ratio estimation (3) inverse reinforcement learning (3) score matching (3) generative adversarial network (3) adversarial learning (2) policy learning (2) conditional generation (2) reinforcement learning (2) contrastive learning (2) likelihood-free inference (2) adversarial training (2) multi-agent reinforcement learning (2)

Papers

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