| Efficient spatially sparse inference for conditional gans and diffusion models M Li, J Lin, C Meng, S Ermon, S Han, JY Zhu Advances in neural information processing systems 35, 28858-28873, 2022 | 1466 | 2022 |
| Gan compression: Efficient architectures for interactive conditional gans M Li, J Lin, Y Ding, Z Liu, JY Zhu, S Han Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2020 | 283 | 2020 |
| Structural characterization of alkaline hydrogen peroxide pretreated grasses exhibiting diverse lignin phenotypes M Li, C Foster, S Kelkar, Y Pu, D Holmes, A Ragauskas, CM Saffron, ... Biotechnology for Biofuels 5 (1), 1-15, 2012 | 143 | 2012 |
| Lite pose: Efficient architecture design for 2d human pose estimation Y Wang, M Li, H Cai, WM Chen, S Han Proceedings of the IEEE/CVF conference on computer vision and pattern …, 2022 | 129 | 2022 |
| Coupling alkaline pre-extraction with alkaline-oxidative post-treatment of corn stover to enhance enzymatic hydrolysis and fermentability T Liu, DL Williams, S Pattathil, M Li, MG Hahn, DB Hodge Biotechnology for biofuels 7, 1-12, 2014 | 62 | 2014 |
| Distrifusion: Distributed parallel inference for high-resolution diffusion models M Li, T Cai, J Cao, Q Zhang, H Cai, J Bai, Y Jia, K Li, S Han Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 46 | 2024 |
| Cell-wall properties contributing to improved deconstruction by alkaline pre-treatment and enzymatic hydrolysis in diverse maize (Zea mays L.) lines M Li, M Heckwolf, JD Crowe, DL Williams, TD Magee, S Kaeppler, ... Journal of Experimental Botany, 2015 | 39 | 2015 |
| Identification of features associated with plant cell wall recalcitrance to pretreatment by alkaline hydrogen peroxide in diverse bioenergy feedstocks using glycome profiling M Li, S Pattathil, MG Hahn, DB Hodge RSC Advances 4 (33), 17282-17292, 2014 | 39 | 2014 |
| Engineered lignin in poplar biomass facilitates Cu-catalyzed alkaline-oxidative pretreatment A Bhalla, N Bansal, S Pattathil, M Li, W Shen, CA Particka, SD Karlen, ... ACS Sustainable Chemistry & Engineering 6 (3), 2932-2941, 2018 | 36 | 2018 |
| Physical fractionation of sweet sorghum and forage/energy sorghum for optimal processing in a biorefinery M Li, G Yan, A Bhalla, L Maldonado-Pereira, PR Russell, SY Ding, ... Industrial Crops and Products 124, 607-616, 2018 | 33 | 2018 |
| Sana: Efficient high-resolution image synthesis with linear diffusion transformers E Xie, J Chen, J Chen, H Cai, H Tang, Y Lin, Z Zhang, M Li, L Zhu, Y Lu, ... arXiv preprint arXiv:2410.10629, 2024 | 13 | 2024 |
| Imaging changes in cell walls of engineered poplar by stimulated Raman scattering and atomic force microscopy W Shen, C Collings, M Li, J Markovicz, J Ralph, SD Mansfield, SY Ding ACS Sustainable Chemistry & Engineering 7 (12), 10616-10622, 2019 | 12 | 2019 |
| Corn stover semi-mechanistic enzymatic hydrolysis model with tight parameter confidence intervals for model-based process design and optimization F Scott, M Li, DL Williams, R Conejeros, DB Hodge, G Aroca Bioresource Technology 177, 255-265, 2015 | 12 | 2015 |
| Deep compression autoencoder for efficient high-resolution diffusion models J Chen, H Cai, J Chen, E Xie, S Yang, H Tang, M Li, Y Lu, S Han arXiv preprint arXiv:2410.10733, 2024 | 11 | 2024 |
| Svdqunat: Absorbing outliers by low-rank components for 4-bit diffusion models M Li, Y Lin, Z Zhang, T Cai, X Li, J Guo, E Xie, C Meng, JY Zhu, S Han arXiv preprint arXiv:2411.05007, 2024 | 10 | 2024 |
| Condition-aware neural network for controlled image generation H Cai, M Li, Q Zhang, MY Liu, S Han Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2024 | 9 | 2024 |
| Prediction of cell wall properties and response to deconstruction using alkaline pretreatment in diverse maize genotypes using Py-MBMS and NIR M Li, DL Williams, M Heckwolf, N de Leon, S Kaeppler, RW Sykes, ... BioEnergy Research 10, 329-343, 2017 | 9 | 2017 |
| Alkaline and alkaline-oxidative pretreatment and hydrolysis of herbaceous biomass for growth of Oleaginous microbes JD Crowe, M Li, DL Williams, AD Smith, T Liu, DB Hodge Microbial Lipid Production: Methods and Protocols, 173-182, 2019 | 3 | 2019 |
| Sparse VideoGen: Accelerating Video Diffusion Transformers with Spatial-Temporal Sparsity H Xi, S Yang, Y Zhao, C Xu, M Li, X Li, Y Lin, H Cai, J Zhang, D Li, J Chen, ... arXiv preprint arXiv:2502.01776, 2025 | 1 | 2025 |
| SANA 1.5: Efficient Scaling of Training-Time and Inference-Time Compute in Linear Diffusion Transformer E Xie, J Chen, Y Zhao, J Yu, L Zhu, Y Lin, Z Zhang, M Li, J Chen, H Cai, ... arXiv preprint arXiv:2501.18427, 2025 | 1 | 2025 |
David B. HodgeProfessor, Chemical Engineering, Montana State UniversityПотвърден имейл адрес: montana.edu