Learning to Interpret Satellite Images using Wikipedia. - Burak Uzkent; Evan Sheehan; Chenlin Meng; Zhongyi Tang; Marshall Burke; David B. Lobell; Stefano Ermon (IJCAI, 2019)

Predicting Economic Development using Geolocated Wikipedia Articles. - Evan Sheehan; Chenlin Meng; Matthew Tan; Burak Uzkent; Neal Jean; Marshall Burke; David B. Lobell; Stefano Ermon (KDD, 2019)

MintNet: Building Invertible Neural Networks with Masked Convolutions. - Yang Song 011; Chenlin Meng; Stefano Ermon (NeurIPS, 2019)

Learning to Interpret Satellite Images in Global Scale Using Wikipedia. - Burak Uzkent; Evan Sheehan; Chenlin Meng; Zhongyi Tang; Marshall Burke; David B. Lobell; Stefano Ermon (CoRR, 2019)

Gaussianization Flows. - Chenlin Meng; Yang Song 011; Jiaming Song; Stefano Ermon (AISTATS, 2020)

Autoregressive Score Matching. - Chenlin Meng; Lantao Yu; Yang Song 011; Jiaming Song; Stefano Ermon (NeurIPS, 2020)

Nonlinear Equation Solving: A Faster Alternative to Feedforward Computation. - Yang Song 011; Chenlin Meng; Renjie Liao; Stefano Ermon (CoRR, 2020)

Geography-Aware Self-Supervised Learning. - Kumar Ayush; Burak Uzkent; Chenlin Meng; Kumar Tanmay; Marshall Burke; David B. Lobell; Stefano Ermon (ICCV, 2021)

Improved Autoregressive Modeling with Distribution Smoothing. - Chenlin Meng; Jiaming Song; Yang Song 011; Shengjia Zhao; Stefano Ermon (ICLR, 2021)

Denoising Diffusion Implicit Models. - Jiaming Song; Chenlin Meng; Stefano Ermon (ICLR, 2021)

Accelerating Feedforward Computation via Parallel Nonlinear Equation Solving. - Yang Song 011; Chenlin Meng; Renjie Liao; Stefano Ermon (ICML, 2021)

Spatial-Temporal Super-Resolution of Satellite Imagery via Conditional Pixel Synthesis. - Yutong He; Dingjie Wang; Nicholas Lai; William Zhang 004; Chenlin Meng; Marshall Burke; David B. Lobell; Stefano Ermon (NeurIPS, 2021)

Estimating High Order Gradients of the Data Distribution by Denoising. - Chenlin Meng; Yang Song 011; Wenzhe Li; Stefano Ermon (NeurIPS, 2021)

D2C: Diffusion-Decoding Models for Few-Shot Conditional Generation. - Abhishek Sinha; Jiaming Song; Chenlin Meng; Stefano Ermon (NeurIPS, 2021)

SustainBench: Benchmarks for Monitoring the Sustainable Development Goals with Machine Learning. - Christopher Yeh; Chenlin Meng; Sherrie Wang; Anne Driscoll; Erik Rozi; Patrick Liu; Jihyeon Janel Lee; Marshall Burke; David B. Lobell; Stefano Ermon (NeurIPS Datasets and Benchmarks, 2021)

D2C: Diffusion-Denoising Models for Few-shot Conditional Generation. - Abhishek Sinha; Jiaming Song; Chenlin Meng; Stefano Ermon (CoRR, 2021)

SDEdit: Image Synthesis and Editing with Stochastic Differential Equations. - Chenlin Meng; Yang Song 011; Jiaming Song; Jiajun Wu 001; Jun-Yan Zhu; Stefano Ermon (CoRR, 2021)

IS-Count: Large-Scale Object Counting from Satellite Images with Covariate-Based Importance Sampling. - Chenlin Meng; Enci Liu; Willie Neiswanger; Jiaming Song; Marshall Burke; David B. Lobell; Stefano Ermon (AAAI, 2022)

Density Ratio Estimation via Infinitesimal Classification. - Kristy Choi; Chenlin Meng; Yang Song 011; Stefano Ermon (AISTATS, 2022)

SDEdit: Guided Image Synthesis and Editing with Stochastic Differential Equations. - Chenlin Meng; Yutong He; Yang Song 011; Jiaming Song; Jiajun Wu 001; Jun-Yan Zhu; Stefano Ermon (ICLR, 2022)

ButterflyFlow: Building Invertible Layers with Butterfly Matrices. - Chenlin Meng; Linqi Zhou; Kristy Choi; Tri Dao; Stefano Ermon (ICML, 2022)

SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery. - Yezhen Cong; Samar Khanna; Chenlin Meng; Patrick Liu; Erik Rozi; Yutong He; Marshall Burke; David B. Lobell; Stefano Ermon (NeurIPS, 2022)

Concrete Score Matching: Generalized Score Matching for Discrete Data. - Chenlin Meng; Kristy Choi; Jiaming Song; Stefano Ermon (NeurIPS, 2022)

Generalizing Bayesian Optimization with Decision-theoretic Entropies. - Willie Neiswanger; Lantao Yu; Shengjia Zhao; Chenlin Meng; Stefano Ermon (NeurIPS, 2022)

Self-Similarity Priors: Neural Collages as Differentiable Fractal Representations. - Michael Poli; Winnie Xu; Stefano Massaroli; Chenlin Meng; Kuno Kim; Stefano Ermon (NeurIPS, 2022)

Tracking Urbanization in Developing Regions with Remote Sensing Spatial-Temporal Super-Resolution. - Yutong He; William Zhang 004; Chenlin Meng; Marshall Burke; David B. Lobell; Stefano Ermon (CoRR, 2022)

On Distillation of Guided Diffusion Models. - Chenlin Meng; Ruiqi Gao; Diederik P. Kingma; Stefano Ermon; Jonathan Ho; Tim Salimans (CoRR, 2022)

On Distillation of Guided Diffusion Models. - Chenlin Meng; Robin Rombach; Ruiqi Gao; Diederik P. Kingma; Stefano Ermon; Jonathan Ho; Tim Salimans (CVPR, 2023)

Dual Diffusion Implicit Bridges for Image-to-Image Translation. - Xuan Su; Jiaming Song; Chenlin Meng; Stefano Ermon (ICLR, 2023)

Holistic Evaluation of Text-to-Image Models. - Tony Lee; Michihiro Yasunaga; Chenlin Meng; Yifan Mai 001; Joon Sung Park; Agrim Gupta; Yunzhi Zhang; Deepak Narayanan; Hannah Teufel; Marco Bellagente; Minguk Kang; Taesung Park; et al. (NeurIPS, 2023)

SIGGRAPH 2023 Course on Diffusion Models. - Chenlin Meng; Jiaming Song; Shuang Li; Jun-Yan Zhu; Stefano Ermon; Tsung-Yi Lin; Chen-Hsuan Lin 001; Karsten Kreis (SIGGRAPH Courses, 2023)

Building Coverage Estimation with Low-resolution Remote Sensing Imagery. - Enci Liu; Chenlin Meng; Matthew Kolodner; Eun Jee Sung; Sihang Chen; Marshall Burke; David B. Lobell; Stefano Ermon (CoRR, 2023)

SSIF: Learning Continuous Image Representation for Spatial-Spectral Super-Resolution. - Gengchen Mai; Ni Lao; Weiwei Sun; Yuchi Ma; Jiaming Song; Chenlin Meng; Hongxu Ma; Jinmeng Rao; Ziyuan Li; Stefano Ermon (CoRR, 2023)

Discrete Diffusion Language Modeling by Estimating the Ratios of the Data Distribution. - Aaron Lou; Chenlin Meng; Stefano Ermon (CoRR, 2023)

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models. - Aarohi Srivastava; Abhinav Rastogi; Abhishek Rao; Abu Awal Md Shoeb; Abubakar Abid; Adam Fisch; Adam R. Brown; Adam Santoro; Aditya Gupta; Adrià Garriga-Alonso; Agnieszka Kluska; Aitor Lewkowycz; et al. (Trans. Mach. Learn. Res., 2023)

Efficient Spatially Sparse Inference for Conditional GANs and Diffusion Models. - Muyang Li; Ji Lin 002; Chenlin Meng; Stefano Ermon; Song Han 003; Jun-Yan Zhu (IEEE Trans. Pattern Anal. Mach. Intell., 2023)

HarvestNet: A Dataset for Detecting Smallholder Farming Activity Using Harvest Piles and Remote Sensing. - Jonathan Xu; Amna Elmustafa; Liya Weldegebriel; Emnet Negash; Richard Lee; Chenlin Meng; Stefano Ermon; David B. Lobell (AAAI, 2024)

DreamPropeller: Supercharge Text-to-3D Generation with Parallel Sampling. - Linqi Zhou; Andy Shih; Chenlin Meng; Stefano Ermon (CVPR, 2024)

DiffusionSat: A Generative Foundation Model for Satellite Imagery. - Samar Khanna; Patrick Liu; Linqi Zhou; Chenlin Meng; Robin Rombach; Marshall Burke; David B. Lobell; Stefano Ermon (ICLR, 2024)

Mastering Text-to-Image Diffusion: Recaptioning, Planning, and Generating with Multimodal LLMs. - Ling Yang 006; Zhaochen Yu; Chenlin Meng; Minkai Xu; Stefano Ermon; Bin Cui 001 (ICML, 2024)

Discrete Diffusion Modeling by Estimating the Ratios of the Data Distribution. - Aaron Lou; Chenlin Meng; Stefano Ermon (ICML, 2024)

Consistency Flow Matching: Defining Straight Flows with Velocity Consistency. - Ling Yang 006; Zixiang Zhang; Zhilong Zhang; Xingchao Liu; Minkai Xu; Wentao Zhang 001; Chenlin Meng; Stefano Ermon; Bin Cui 001 (CoRR, 2024)

SVDQuant: Absorbing Outliers by Low-Rank Components for 4-Bit Diffusion Models. - Muyang Li; Yujun Lin 001; Zhekai Zhang; Tianle Cai; Xiuyu Li; Junxian Guo; Enze Xie; Chenlin Meng; Jun-Yan Zhu; Song Han 003 (CoRR, 2024)

Keyframe-Guided Creative Video Inpainting. - Yuwei Guo 002; Ceyuan Yang; Anyi Rao; Chenlin Meng; Omer Bar-Tal; Shuangrui Ding; Maneesh Agrawala; Dahua Lin; Bo Dai 002 (CVPR, 2025)

Improving Diffusion Inverse Problem Solving with Decoupled Noise Annealing. - Bingliang Zhang; Wenda Chu; Julius Berner; Chenlin Meng; Anima Anandkumar; Yang Song 011 (CVPR, 2025)

AuroraCap: Efficient, Performant Video Detailed Captioning and a New Benchmark. - Wenhao Chai; Enxin Song; Yilun Du; Chenlin Meng; Vashisht Madhavan; Omer Bar-Tal; Jenq-Neng Hwang; Saining Xie; Christopher D. Manning (ICLR, 2025)

SVDQuant: Absorbing Outliers by Low-Rank Component for 4-Bit Diffusion Models. - Muyang Li; Yujun Lin 001; Zhekai Zhang; Tianle Cai; Xiuyu Li; Junxian Guo; Enze Xie; Chenlin Meng; Jun-Yan Zhu; Song Han 001 (ICLR, 2025)

Breakthrough in fine-grained video anomaly detection on highway: New benchmark and model. - Chenlin Meng; Xin Wang; Chi Zhang; Zhaoyong Mao; Junge Shen; Zhiyong Cheng 008 (Expert Syst. Appl., 2026)