Meng, Chenlin

Denoising Diffusion Implicit Models

Song, J., Meng, C., & Ermon, S. (2020) · arXiv

Generative Adversarial Networks and Image SynthesisImage and Signal Denoising Methods

Cited by 2,507

Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models

Srivastava, A., Rastogi, A., Rao, A., Shoeb, A. A. M., Abid, A., Fisch, A., Brown, A. R., Santoro, A., Gupta, A., Garriga-Alonso, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 569

SatMAE: Pre-training Transformers for Temporal and Multi-Spectral Satellite Imagery

Cong, Y., Khanna, S., Meng, C., Liu, P., Rozi, E., He, Y., Burke, M., Lobell, D. B., & Ermon, S. (2022) · arXiv

Remote-Sensing Image ClassificationRemote Sensing in Agriculture

Cited by 323

SatMAE: Pre-Training Transformers for Temporal and Multi-Spectral Satellite Imagery

Cong, Y., Khanna, S., Meng, C., Liu, P., Rozi, E., He, Y., Burke, M., Lobell, D., & Ermon, S. (2022) · Advances in Neural Information Processing Systems 35

Remote-Sensing Image ClassificationRemote Sensing in Agriculture

Cited by 303

Geography-Aware Self-Supervised Learning

Ayush, K., Uzkent, B., Meng, C., Tanmay, K., Burke, M., Lobell, D., & Ermon, S. (2021) · 2021 IEEE/CVF International Conference on Computer Vision (ICCV)

Domain Adaptation and Few-Shot LearningRemote-Sensing Image Classification

Cited by 288

D2C: Diffusion-Denoising Models for Few-shot Conditional Generation

Sinha, A., Song, J., Meng, C., & Ermon, S. (2021) · arXiv

Generative Adversarial Networks and Image SynthesisDomain Adaptation and Few-Shot Learning

Cited by 10