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2020 – today
- 2024
[j10]Zhuoran Qiao
, Weili Nie, Arash Vahdat, Thomas F. Miller III, Animashree Anandkumar:
State-specific protein-ligand complex structure prediction with a multiscale deep generative model. Nat. Mac. Intell. 6(2): 195-208 (2024)- [j9]Shengchao Liu, Chengpeng Wang, Jiarui Lu, Weili Nie, Hanchen Wang, Zhuoxinran Li, Bolei Zhou, Jian Tang:
Unsupervised Discovery of Steerable Factors When Graph Deep Generative Models Are Entangled. Trans. Mach. Learn. Res. 2024 (2024) - [j8]Hongkai Zheng, Weili Nie, Arash Vahdat, Anima Anandkumar:
Fast Training of Diffusion Models with Masked Transformers. Trans. Mach. Learn. Res. 2024 (2024) - [c25]Sihyun Yu, Weili Nie, De-An Huang, Boyi Li, Jinwoo Shin, Anima Anandkumar:
Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition. ICLR 2024 - [c24]Weili Nie, Sifei Liu, Morteza Mardani, Chao Liu, Benjamin Eckart, Arash Vahdat:
Compositional Text-to-Image Generation with Dense Blob Representations. ICML 2024 - [c23]Chao Liu, Weili Nie, Sifei Liu, Abhishek Badki, Hang Su, Morteza Mardani, Benjamin Eckart, Arash Vahdat:
BlobGEN-3D: Compositional 3D-Consistent Freeview Image Generation with 3D Blobs. SIGGRAPH Asia 2024: 36:1-36:11 - [c22]Omri Avrahami, Rinon Gal, Gal Chechik, Ohad Fried, Dani Lischinski, Arash Vahdat, Weili Nie:
DiffUHaul: A Training-Free Method for Object Dragging in Images. SIGGRAPH Asia 2024: 38:1-38:12 - [i36]Shengchao Liu, Chengpeng Wang, Jiarui Lu, Weili Nie, Hanchen Wang, Zhuoxinran Li, Bolei Zhou, Jian Tang:
Unsupervised Discovery of Steerable Factors When Graph Deep Generative Models Are Entangled. CoRR abs/2401.17123 (2024) - [i35]Zizheng Pan, Bohan Zhuang, De-An Huang, Weili Nie, Zhiding Yu, Chaowei Xiao, Jianfei Cai, Anima Anandkumar:
T-Stitch: Accelerating Sampling in Pre-Trained Diffusion Models with Trajectory Stitching. CoRR abs/2402.14167 (2024) - [i34]Sihyun Yu, Weili Nie, De-An Huang, Boyi Li, Jinwoo Shin, Anima Anandkumar:
Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition. CoRR abs/2403.14148 (2024) - [i33]Weili Nie, Sifei Liu, Morteza Mardani, Chao Liu, Benjamin Eckart, Arash Vahdat:
Compositional Text-to-Image Generation with Dense Blob Representations. CoRR abs/2405.08246 (2024) - [i32]Omri Avrahami, Rinon Gal, Gal Chechik, Ohad Fried, Dani Lischinski, Arash Vahdat, Weili Nie:
DiffUHaul: A Training-Free Method for Object Dragging in Images. CoRR abs/2406.01594 (2024) - [i31]Dejia Xu, Weili Nie, Chao Liu, Sifei Liu, Jan Kautz, Zhangyang Wang, Arash Vahdat:
CamCo: Camera-Controllable 3D-Consistent Image-to-Video Generation. CoRR abs/2406.02509 (2024) - [i30]Siyi Gu, Minkai Xu, Alexander S. Powers, Weili Nie, Tomas Geffner, Karsten Kreis, Jure Leskovec, Arash Vahdat, Stefano Ermon:
Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization. CoRR abs/2407.01648 (2024) - [i29]Sangyun Lee, Yilun Xu, Tomas Geffner, Giulia Fanti, Karsten Kreis, Arash Vahdat, Weili Nie:
Truncated Consistency Models. CoRR abs/2410.14895 (2024) - [i28]Giannis Daras, Weili Nie, Karsten Kreis, Alex Dimakis, Morteza Mardani, Nikola Borislavov Kovachki, Arash Vahdat:
Warped Diffusion: Solving Video Inverse Problems with Image Diffusion Models. CoRR abs/2410.16152 (2024) - [i27]Minkai Xu, Tomas Geffner, Karsten Kreis, Weili Nie, Yilun Xu, Jure Leskovec, Stefano Ermon, Arash Vahdat:
Energy-Based Diffusion Language Models for Text Generation. CoRR abs/2410.21357 (2024) - [i26]Yanke Song, Jonathan Lorraine, Weili Nie, Karsten Kreis, James Lucas:
Multi-student Diffusion Distillation for Better One-step Generators. CoRR abs/2410.23274 (2024) - 2023
- [j7]Maxim Zvyagin, Alexander Brace, Kyle Hippe, Yuntian Deng, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, Defne G. Ozgulbas, Natalia Vassilieva, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Sam Foreman, Zhen Xie, Diangen Lin, Maulik Shukla, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Rick Stevens, Anima Anandkumar, Venkatram Vishwanath, Arvind Ramanathan:
GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics. Int. J. High Perform. Comput. Appl. 37(6): 683-705 (2023) - [j6]Shengchao Liu, Weili Nie, Chengpeng Wang, Jiarui Lu, Zhuoran Qiao, Ling Liu, Jian Tang, Chaowei Xiao, Animashree Anandkumar:
Multi-modal molecule structure-text model for text-based retrieval and editing. Nat. Mac. Intell. 5(12): 1447-1457 (2023) - [j5]Yuji Roh, Weili Nie, De-An Huang, Steven Euijong Whang, Arash Vahdat, Anima Anandkumar:
Dr-Fairness: Dynamic Data Ratio Adjustment for Fair Training on Real and Generated Data. Trans. Mach. Learn. Res. 2023 (2023) - [c21]Zhuolin Yang, Wei Ping, Zihan Liu, Vijay Korthikanti, Weili Nie, De-An Huang, Linxi Fan, Zhiding Yu, Shiyi Lan, Bo Li, Mohammad Shoeybi, Ming-Yu Liu, Yuke Zhu, Bryan Catanzaro, Chaowei Xiao, Anima Anandkumar:
Re-ViLM: Retrieval-Augmented Visual Language Model for Zero and Few-Shot Image Captioning. EMNLP (Findings) 2023: 11844-11857 - [c20]Zichao Wang, Weili Nie, Zhuoran Qiao, Chaowei Xiao, Richard G. Baraniuk, Anima Anandkumar:
Retrieval-based Controllable Molecule Generation. ICLR 2023 - [c19]Shutong Wu, Jiongxiao Wang, Wei Ping, Weili Nie, Chaowei Xiao:
Defending against Adversarial Audio via Diffusion Model. ICLR 2023 - [c18]Chaowei Xiao, Zhongzhu Chen, Kun Jin, Jiongxiao Wang, Weili Nie, Mingyan Liu, Anima Anandkumar, Bo Li, Dawn Song:
DensePure: Understanding Diffusion Models for Adversarial Robustness. ICLR 2023 - [c17]Guan-Horng Liu, Arash Vahdat, De-An Huang, Evangelos A. Theodorou, Weili Nie, Anima Anandkumar:
I2SB: Image-to-Image Schrödinger Bridge. ICML 2023: 22042-22062 - [c16]Jiachen Sun, Jiongxiao Wang, Weili Nie, Zhiding Yu, Zhuoqing Mao, Chaowei Xiao:
A Critical Revisit of Adversarial Robustness in 3D Point Cloud Recognition with Diffusion-Driven Purification. ICML 2023: 33100-33114 - [c15]Hongkai Zheng, Weili Nie, Arash Vahdat, Kamyar Azizzadenesheli, Anima Anandkumar:
Fast Sampling of Diffusion Models via Operator Learning. ICML 2023: 42390-42402 - [d1]Zhuoran Qiao, Weili Nie, Arash Vahdat, Thomas F. Miller III, Animashree Anandkumar:
NeuralPLexer evaluation datasets and predictions. Zenodo, 2023
- [i25]Shengchao Liu, Yutao Zhu, Jiarui Lu, Zhao Xu, Weili Nie, Anthony Gitter, Chaowei Xiao, Jian Tang, Hongyu Guo, Anima Anandkumar:
A Text-guided Protein Design Framework. CoRR abs/2302.04611 (2023) - [i24]Zhuolin Yang, Wei Ping, Zihan Liu, Vijay Korthikanti, Weili Nie, De-An Huang, Linxi Fan, Zhiding Yu, Shiyi Lan, Bo Li, Ming-Yu Liu, Yuke Zhu, Mohammad Shoeybi, Bryan Catanzaro, Chaowei Xiao, Anima Anandkumar:
Re-ViLM: Retrieval-Augmented Visual Language Model for Zero and Few-Shot Image Captioning. CoRR abs/2302.04858 (2023) - [i23]Guan-Horng Liu, Arash Vahdat, De-An Huang, Evangelos A. Theodorou, Weili Nie, Anima Anandkumar:
I2SB: Image-to-Image Schrödinger Bridge. CoRR abs/2302.05872 (2023) - [i22]Shutong Wu, Jiongxiao Wang, Wei Ping, Weili Nie, Chaowei Xiao:
Defending against Adversarial Audio via Diffusion Model. CoRR abs/2303.01507 (2023) - [i21]Hongkai Zheng, Weili Nie, Arash Vahdat, Anima Anandkumar:
Fast Training of Diffusion Models with Masked Transformers. CoRR abs/2306.09305 (2023) - [i20]Sascha Diefenbacher, Guan-Horng Liu, Vinicius Mikuni, Benjamin Nachman, Weili Nie:
Improving Generative Model-based Unfolding with Schrödinger Bridges. CoRR abs/2308.12351 (2023) - [i19]Shuaiwen Leon Song, Bonnie Kruft, Minjia Zhang, Conglong Li, Shiyang Chen, Chengming Zhang, Masahiro Tanaka, Xiaoxia Wu, Jeff Rasley, Ammar Ahmad Awan, Connor Holmes, Martin Cai, Adam Ghanem, Zhongzhu Zhou, Yuxiong He, Pete Luferenko, Divya Kumar, Jonathan A. Weyn, Ruixiong Zhang, Sylwester Klocek, Volodymyr Vragov, Mohammed AlQuraishi, Gustaf Ahdritz, Christina Floristean, Cristina Negri, Rao Kotamarthi, Venkatram Vishwanath, Arvind Ramanathan, Sam Foreman, Kyle Hippe, Troy Arcomano, Romit Maulik, Maxim Zvyagin, Alexander Brace, Bin Zhang, Cindy Orozco Bohorquez, Austin Clyde, Bharat Kale, Danilo Perez-Rivera, Heng Ma, Carla M. Mann, Michael W. Irvin, J. Gregory Pauloski, Logan T. Ward, Valérie Hayot-Sasson, Murali Emani, Zhen Xie, Diangen Lin, Maulik Shukla, Ian T. Foster, James J. Davis, Michael E. Papka, Thomas S. Brettin, Prasanna Balaprakash, Gina Tourassi, John Gounley, Heidi A. Hanson, Thomas E. Potok, Massimiliano Lupo Pasini, Kate Evans, Dan Lu, Dalton D. Lunga, Junqi Yin, Sajal Dash, Feiyi Wang, Mallikarjun Shankar, Isaac Lyngaas, Xiao Wang, Guojing Cong, Pei Zhang, Ming Fan, Siyan Liu, Adolfy Hoisie, Shinjae Yoo, Yihui Ren, William Tang, Kyle Felker, Alexey Svyatkovskiy, Hang Liu, Ashwin M. Aji, Angela Dalton, Michael J. Schulte, Karl Schulz, Yuntian Deng, Weili Nie, Josh Romero, Christian Dallago, Arash Vahdat, Chaowei Xiao, Thomas Gibbs, Anima Anandkumar, Rick Stevens:
DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. CoRR abs/2310.04610 (2023) - 2022
- [c14]Huaizu Jiang, Xiaojian Ma, Weili Nie, Zhiding Yu, Yuke Zhu, Anima Anandkumar:
Bongard-HOI: Benchmarking Few-Shot Visual Reasoning for Human-Object Interactions. CVPR 2022: 19034-19043 - [c13]Xiaojian Ma, Weili Nie, Zhiding Yu, Huaizu Jiang, Chaowei Xiao, Yuke Zhu, Song-Chun Zhu, Anima Anandkumar:
RelViT: Concept-guided Vision Transformer for Visual Relational Reasoning. ICLR 2022 - [c12]Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Animashree Anandkumar:
Diffusion Models for Adversarial Purification. ICML 2022: 16805-16827 - [c11]Manli Shu, Weili Nie, De-An Huang, Zhiding Yu, Tom Goldstein, Anima Anandkumar, Chaowei Xiao:
Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models. NeurIPS 2022 - [i18]Xiaojian Ma, Weili Nie, Zhiding Yu, Huaizu Jiang, Chaowei Xiao, Yuke Zhu, Song-Chun Zhu, Anima Anandkumar:
RelViT: Concept-guided Vision Transformer for Visual Relational Reasoning. CoRR abs/2204.11167 (2022) - [i17]Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar:
Diffusion Models for Adversarial Purification. CoRR abs/2205.07460 (2022) - [i16]Huaizu Jiang, Xiaojian Ma, Weili Nie, Zhiding Yu, Yuke Zhu, Anima Anandkumar:
Bongard-HOI: Benchmarking Few-Shot Visual Reasoning for Human-Object Interactions. CoRR abs/2205.13803 (2022) - [i15]Jiachen Sun, Weili Nie, Zhiding Yu, Z. Morley Mao, Chaowei Xiao:
PointDP: Diffusion-driven Purification against Adversarial Attacks on 3D Point Cloud Recognition. CoRR abs/2208.09801 (2022) - [i14]Zichao Wang, Weili Nie, Zhuoran Qiao, Chaowei Xiao, Richard G. Baraniuk, Anima Anandkumar:
Retrieval-based Controllable Molecule Generation. CoRR abs/2208.11126 (2022) - [i13]Manli Shu, Weili Nie, De-An Huang, Zhiding Yu, Tom Goldstein, Anima Anandkumar, Chaowei Xiao:
Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models. CoRR abs/2209.07511 (2022) - [i12]Zhuoran Qiao, Weili Nie, Arash Vahdat, Thomas F. Miller III, Anima Anandkumar:
Dynamic-Backbone Protein-Ligand Structure Prediction with Multiscale Generative Diffusion Models. CoRR abs/2209.15171 (2022) - [i11]Chaowei Xiao, Zhongzhu Chen, Kun Jin, Jiongxiao Wang, Weili Nie, Mingyan Liu, Anima Anandkumar, Bo Li, Dawn Song:
DensePure: Understanding Diffusion Models towards Adversarial Robustness. CoRR abs/2211.00322 (2022) - [i10]Hongkai Zheng, Weili Nie, Arash Vahdat, Kamyar Azizzadenesheli, Anima Anandkumar:
Fast Sampling of Diffusion Models via Operator Learning. CoRR abs/2211.13449 (2022) - [i9]Shengchao Liu, Weili Nie, Chengpeng Wang, Jiarui Lu, Zhuoran Qiao, Ling Liu, Jian Tang, Chaowei Xiao, Anima Anandkumar:
Multi-modal Molecule Structure-text Model for Text-based Retrieval and Editing. CoRR abs/2212.10789 (2022) - 2021
- [c10]Weili Nie, Arash Vahdat, Anima Anandkumar:
Controllable and Compositional Generation with Latent-Space Energy-Based Models. NeurIPS 2021: 13497-13510 - [i8]Weili Nie, Arash Vahdat, Anima Anandkumar:
Controllable and Compositional Generation with Latent-Space Energy-Based Models. CoRR abs/2110.10873 (2021) - 2020
- [c9]Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit B. Patel, Animashree Anandkumar:
Semi-Supervised StyleGAN for Disentanglement Learning. ICML 2020: 7360-7369 - [c8]Weili Nie, Zhiding Yu, Lei Mao, Ankit B. Patel, Yuke Zhu, Anima Anandkumar:
Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning. NeurIPS 2020 - [i7]Weili Nie, Tero Karras, Animesh Garg, Shoubhik Debnath, Anjul Patney, Ankit B. Patel, Anima Anandkumar:
Semi-Supervised StyleGAN for Disentanglement Learning. CoRR abs/2003.03461 (2020) - [i6]Weili Nie, Zichao Wang, Ankit B. Patel, Richard G. Baraniuk:
An Improved Semi-Supervised VAE for Learning Disentangled Representations. CoRR abs/2006.07460 (2020) - [i5]Weili Nie, Zhiding Yu, Lei Mao, Ankit B. Patel, Yuke Zhu, Animashree Anandkumar:
Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning. CoRR abs/2010.00763 (2020)
2010 – 2019
- 2019
- [c7]Weili Nie, Nina Narodytska, Ankit Patel:
RelGAN: Relational Generative Adversarial Networks for Text Generation. ICLR (Poster) 2019 - [c6]Weili Nie, Ankit Patel:
Towards a Better Understanding and Regularization of GAN Training Dynamics. UAI 2019: 281-291 - 2018
- [c5]Weili Nie, Yang Zhang, Ankit Patel:
A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations. ICML 2018: 3806-3815 - [c4]Zichao Wang, Andrew S. Lan, Weili Nie, Andrew E. Waters, Phillip J. Grimaldi, Richard G. Baraniuk:
QG-net: a data-driven question generation model for educational content. L@S 2018: 7:1-7:10 - [i4]Weili Nie, Yang Zhang, Ankit Patel:
A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations. CoRR abs/1805.07039 (2018) - [i3]Weili Nie, Ankit Patel:
JR-GAN: Jacobian Regularization for Generative Adversarial Networks. CoRR abs/1806.09235 (2018) - 2017
- [j4]Yi Zhong, Martin Haenggi, Fu-Chun Zheng, Wenyi Zhang, Tony Q. S. Quek, Weili Nie:
Toward a Tractable Delay Analysis in Ultra-Dense Networks. IEEE Commun. Mag. 55(12): 103-109 (2017) - [j3]Lan Zhang, Weili Nie, Gang Feng, Fu-Chun Zheng, Shuang Qin:
Uplink Performance Improvement by Decoupling Uplink/Downlink Access in HetNets. IEEE Trans. Veh. Technol. 66(8): 6862-6876 (2017) - 2016
- [j2]Weili Nie, Fu-Chun Zheng, Xiaoming Wang, Wenyi Zhang, Shi Jin:
User-Centric Cross-Tier Base Station Clustering and Cooperation in Heterogeneous Networks: Rate Improvement and Energy Saving. IEEE J. Sel. Areas Commun. 34(5): 1192-1206 (2016) - [j1]Weili Nie, Yi Zhong, Fu-Chun Zheng, Wenyi Zhang, Timothy O'Farrell:
HetNets With Random DTX Scheme: Local Delay and Energy Efficiency. IEEE Trans. Veh. Technol. 65(8): 6601-6613 (2016) - [i2]Yi Zhong, Martin Haenggi, Fu-Chun Zheng, Wenyi Zhang, Tony Q. S. Quek, Weili Nie:
Towards a Tractable Delay Analysis in Large Wireless Networks. CoRR abs/1612.01276 (2016) - 2015
- [c3]Lan Zhang, Gang Feng, Weili Nie, Shuang Qin:
A Comparison Study of Coupled and Decoupled Uplink-Downlink Access in Heterogeneous Cellular Networks. GLOBECOM 2015: 1-7 - [c2]Weili Nie, Yi Zhong, Fu-Chun Zheng, Wenyi Zhang:
Local delay and energy efficiency analysis in HetNets with random DTX scheme. ICC 2015: 1857-1862 - 2014
- [c1]Weili Nie, Xiaoming Wang, Fu-Chun Zheng, Wenyi Zhang:
Energy-efficient base station cooperation in downlink heterogeneous cellular networks. GLOBECOM 2014: 1779-1784 - [i1]Weili Nie, Fu-Chun Zheng, Xiaoming Wang, Shi Jin, Wenyi Zhang:
Energy Efficiency of Cross-Tier Base Station Cooperation in Heterogeneous Cellular Networks. CoRR abs/1406.1867 (2014)
Coauthor Index
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