Energy-efficient base station cooperation in downlink heterogeneous cellular networks. - Weili Nie; Xiaoming Wang 011; Fu-Chun Zheng; Wenyi Zhang 001 (GLOBECOM, 2014)

Energy Efficiency of Cross-Tier Base Station Cooperation in Heterogeneous Cellular Networks. - Weili Nie; Fu-Chun Zheng; Xiaoming Wang 011; Shi Jin 002; Wenyi Zhang 001 (CoRR, 2014)

A Comparison Study of Coupled and Decoupled Uplink-Downlink Access in Heterogeneous Cellular Networks. - Lan Zhang 005; Gang Feng 004; Weili Nie; Shuang Qin (GLOBECOM, 2015)

Local delay and energy efficiency analysis in HetNets with random DTX scheme. - Weili Nie; Yi Zhong 001; Fu-Chun Zheng; Wenyi Zhang 001 (ICC, 2015)

Towards a Tractable Delay Analysis in Large Wireless Networks. - Yi Zhong 001; Martin Haenggi; Fu-Chun Zheng; Wenyi Zhang 001; Tony Q. S. Quek; Weili Nie (CoRR, 2016)

User-Centric Cross-Tier Base Station Clustering and Cooperation in Heterogeneous Networks: Rate Improvement and Energy Saving. - Weili Nie; Fu-Chun Zheng; Xiaoming Wang 011; Wenyi Zhang 001; Shi Jin 002 (IEEE J. Sel. Areas Commun., 2016)

HetNets With Random DTX Scheme: Local Delay and Energy Efficiency. - Weili Nie; Yi Zhong 001; Fu-Chun Zheng; Wenyi Zhang 001; Timothy O'Farrell (IEEE Trans. Veh. Technol., 2016)

Toward a Tractable Delay Analysis in Ultra-Dense Networks. - Yi Zhong 001; Martin Haenggi; Fu-Chun Zheng; Wenyi Zhang 001; Tony Q. S. Quek; Weili Nie (IEEE Commun. Mag., 2017)

Uplink Performance Improvement by Decoupling Uplink/Downlink Access in HetNets. - Lan Zhang 005; Weili Nie; Gang Feng 004; Fu-Chun Zheng; Shuang Qin (IEEE Trans. Veh. Technol., 2017)

A Theoretical Explanation for Perplexing Behaviors of Backpropagation-based Visualizations. - Weili Nie; Yang Zhang; Ankit Patel (ICML, 2018)

QG-net: a data-driven question generation model for educational content. - Zichao Wang 001; Andrew S. Lan; Weili Nie; Andrew E. Waters; Phillip J. Grimaldi; Richard G. Baraniuk (L@S, 2018)

JR-GAN: Jacobian Regularization for Generative Adversarial Networks. - Weili Nie; Ankit Patel (CoRR, 2018)

RelGAN: Relational Generative Adversarial Networks for Text Generation. - Weili Nie; Nina Narodytska; Ankit Patel (ICLR (Poster), 2019)

Towards a Better Understanding and Regularization of GAN Training Dynamics. - Weili Nie; Ankit Patel (UAI, 2019)

Semi-Supervised StyleGAN for Disentanglement Learning. - Weili Nie; Tero Karras; Animesh Garg; Shoubhik Debnath; Anjul Patney; Ankit B. Patel; Animashree Anandkumar (ICML, 2020)

Bongard-LOGO: A New Benchmark for Human-Level Concept Learning and Reasoning. - Weili Nie; Zhiding Yu; Lei Mao; Ankit B. Patel; Yuke Zhu; Anima Anandkumar (NeurIPS, 2020)

An Improved Semi-Supervised VAE for Learning Disentangled Representations. - Weili Nie; Zichao Wang 001; Ankit B. Patel; Richard G. Baraniuk (CoRR, 2020)

Controllable and Compositional Generation with Latent-Space Energy-Based Models. - Weili Nie; Arash Vahdat; Anima Anandkumar (NeurIPS, 2021)

Bongard-HOI: Benchmarking Few-Shot Visual Reasoning for Human-Object Interactions. - Huaizu Jiang; Xiaojian Ma 001; Weili Nie; Zhiding Yu; Yuke Zhu; Anima Anandkumar (CVPR, 2022)

RelViT: Concept-guided Vision Transformer for Visual Relational Reasoning. - Xiaojian Ma 001; Weili Nie; Zhiding Yu; Huaizu Jiang; Chaowei Xiao; Yuke Zhu; Song-Chun Zhu; Anima Anandkumar (ICLR, 2022)

Diffusion Models for Adversarial Purification. - Weili Nie; Brandon Guo; Yujia Huang; Chaowei Xiao; Arash Vahdat; Animashree Anandkumar (ICML, 2022)

Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models. - Manli Shu; Weili Nie; De-An Huang; Zhiding Yu; Tom Goldstein; Anima Anandkumar; Chaowei Xiao (NeurIPS, 2022)

PointDP: Diffusion-driven Purification against Adversarial Attacks on 3D Point Cloud Recognition. - Jiachen Sun; Weili Nie; Zhiding Yu; Z. Morley Mao; Chaowei Xiao (CoRR, 2022)

Dynamic-Backbone Protein-Ligand Structure Prediction with Multiscale Generative Diffusion Models. - Zhuoran Qiao; Weili Nie; Arash Vahdat; Thomas F. Miller III; Anima Anandkumar (CoRR, 2022)

DensePure: Understanding Diffusion Models towards Adversarial Robustness. - Chaowei Xiao; Zhongzhu Chen; Kun Jin; Jiongxiao Wang; Weili Nie; Mingyan Liu; Anima Anandkumar; Bo Li 026; Dawn Song (CoRR, 2022)

Re-ViLM: Retrieval-Augmented Visual Language Model for Zero and Few-Shot Image Captioning. - Zhuolin Yang; Wei Ping; Zihan Liu 001; Vijay Korthikanti; Weili Nie; De-An Huang; Linxi Fan; Zhiding Yu; Shiyi Lan; Bo Li 026; Mohammad Shoeybi; Ming-Yu Liu 001; et al. (EMNLP (Findings), 2023)

Retrieval-based Controllable Molecule Generation. - Zichao Wang 001; Weili Nie; Zhuoran Qiao; Chaowei Xiao; Richard G. Baraniuk; Anima Anandkumar (ICLR, 2023)

Defending against Adversarial Audio via Diffusion Model. - Shutong Wu; Jiongxiao Wang; Wei Ping; Weili Nie; Chaowei Xiao (ICLR, 2023)

DensePure: Understanding Diffusion Models for Adversarial Robustness. - Chaowei Xiao; Zhongzhu Chen; Kun Jin; Jiongxiao Wang; Weili Nie; Mingyan Liu; Anima Anandkumar; Bo Li 026; Dawn Song (ICLR, 2023)

I2SB: Image-to-Image Schrödinger Bridge. - Guan-Horng Liu; Arash Vahdat; De-An Huang; Evangelos A. Theodorou; Weili Nie; Anima Anandkumar (ICML, 2023)

A Critical Revisit of Adversarial Robustness in 3D Point Cloud Recognition with Diffusion-Driven Purification. - Jiachen Sun; Jiongxiao Wang; Weili Nie; Zhiding Yu; Zhuoqing Mao 001; Chaowei Xiao (ICML, 2023)

Fast Sampling of Diffusion Models via Operator Learning. - Hongkai Zheng; Weili Nie; Arash Vahdat; Kamyar Azizzadenesheli; Anima Anandkumar (ICML, 2023)

A Text-guided Protein Design Framework. - Shengchao Liu; Yutao Zhu 001; Jiarui Lu; Zhao Xu 005; Weili Nie; Anthony Gitter; Chaowei Xiao; Jian Tang 005; Hongyu Guo; Anima Anandkumar (CoRR, 2023)

Improving Generative Model-based Unfolding with Schrödinger Bridges. - Sascha Diefenbacher; Guan-Horng Liu; Vinicius Mikuni; Benjamin Nachman; Weili Nie (CoRR, 2023)

DeepSpeed4Science Initiative: Enabling Large-Scale Scientific Discovery through Sophisticated AI System Technologies. - Shuaiwen Leon Song; Bonnie Kruft; Minjia Zhang; Conglong Li; Shiyang Chen 004; Chengming Zhang 006; Masahiro Tanaka; Xiaoxia Wu; Jeff Rasley; Ammar Ahmad Awan; Connor Holmes; Martin Cai; et al. (CoRR, 2023)

Dr-Fairness: Dynamic Data Ratio Adjustment for Fair Training on Real and Generated Data. - Yuji Roh; Weili Nie; De-An Huang; Steven Euijong Whang; Arash Vahdat; Anima Anandkumar (Trans. Mach. Learn. Res., 2023)

NeuralPLexer evaluation datasets and predictions. - Zhuoran Qiao; Weili Nie; Arash Vahdat; Thomas F. Miller III; Animashree Anandkumar (Zenodo, 2023)

GenSLMs: Genome-scale language models reveal SARS-CoV-2 evolutionary dynamics. - 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; et al. (Int. J. High Perform. Comput. Appl., 2023)

NeuralPLexer evaluation datasets and predictions. - Zhuoran Qiao; Weili Nie; Arash Vahdat; Thomas F. Miller III; Animashree Anandkumar (Zenodo, 2023)

Multi-modal molecule structure-text model for text-based retrieval and editing. - Shengchao Liu; Weili Nie; Chengpeng Wang; Jiarui Lu; Zhuoran Qiao; Ling Liu 001; Jian Tang 005; Chaowei Xiao; Animashree Anandkumar (Nat. Mac. Intell., 2023)

Compositional Text-to-Image Generation with Feedforward Layout Generation. - Sifei Liu; Weili Nie; An-Chieh Cheng; Morteza Mardani; Chao Liu 064; Benjamin Eckart; Arash Vahdat (ECCV Workshops (11), 2024)

Efficient Video Diffusion Models via Content-Frame Motion-Latent Decomposition. - Sihyun Yu; Weili Nie; De-An Huang; Boyi Li; Jinwoo Shin; Anima Anandkumar (ICLR, 2024)

Compositional Text-to-Image Generation with Dense Blob Representations. - Weili Nie; Sifei Liu; Morteza Mardani; Chao Liu 064; Benjamin Eckart; Arash Vahdat (ICML, 2024)

Warped Diffusion: Solving Video Inverse Problems with Image Diffusion Models. - Giannis Daras; Weili Nie; Karsten Kreis; Alex Dimakis; Morteza Mardani; Nikola B. Kovachki; Arash Vahdat (NeurIPS, 2024)

Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization. - Siyi Gu; Minkai Xu; Alexander S. Powers; Weili Nie; Tomas Geffner; Karsten Kreis; Jure Leskovec; Arash Vahdat; Stefano Ermon (NeurIPS, 2024)

Molecule Generation with Fragment Retrieval Augmentation. - Seul Lee; Karsten Kreis; Srimukh Prasad Veccham; Meng Liu 015; Danny Reidenbach; Saee Paliwal; Arash Vahdat; Weili Nie (NeurIPS, 2024)

BlobGEN-3D: Compositional 3D-Consistent Freeview Image Generation with 3D Blobs. - Chao Liu 064; Weili Nie; Sifei Liu; Abhishek Badki; Hang Su 005; Morteza Mardani; Benjamin Eckart; Arash Vahdat (SIGGRAPH Asia, 2024)

DiffUHaul: A Training-Free Method for Object Dragging in Images. - Omri Avrahami; Rinon Gal; Gal Chechik; Ohad Fried; Dani Lischinski; Arash Vahdat; Weili Nie (SIGGRAPH Asia, 2024)

CamCo: Camera-Controllable 3D-Consistent Image-to-Video Generation. - Dejia Xu; Weili Nie; Chao Liu 064; Sifei Liu; Jan Kautz; Zhangyang Wang; Arash Vahdat (CoRR, 2024)

Multi-student Diffusion Distillation for Better One-step Generators. - Yanke Song; Jonathan Lorraine; Weili Nie; Karsten Kreis; James Lucas (CoRR, 2024)

State-specific protein-ligand complex structure prediction with a multiscale deep generative model. - Zhuoran Qiao; Weili Nie; Arash Vahdat; Thomas F. Miller III; Animashree Anandkumar (Nat. Mac. Intell., 2024)

Unsupervised Discovery of Steerable Factors When Graph Deep Generative Models Are Entangled. - Shengchao Liu; Chengpeng Wang; Jiarui Lu; Weili Nie; Hanchen Wang 002; Zhuoxinran Li; Bolei Zhou; Jian Tang 005 (Trans. Mach. Learn. Res., 2024)

Fast Training of Diffusion Models with Masked Transformers. - Hongkai Zheng; Weili Nie; Arash Vahdat; Anima Anandkumar (Trans. Mach. Learn. Res., 2024)

BlobGEN-Vid: Compositional Text-to-Video Generation with Blob Video Representations. - Weixi Feng; Chao Liu 064; Sifei Liu; William Yang Wang; Arash Vahdat; Weili Nie (CVPR, 2025)

Truncated Consistency Models. - Sangyun Lee; Yilun Xu; Tomas Geffner; Giulia Fanti; Karsten Kreis; Arash Vahdat; Weili Nie (ICLR, 2025)

T-Stitch: Accelerating Sampling in Pre-Trained Diffusion Models with Trajectory Stitching. - Zizheng Pan; Bohan Zhuang; De-An Huang; Weili Nie; Zhiding Yu; Chaowei Xiao; Jianfei Cai 001; Anima Anandkumar (ICLR, 2025)

Energy-Based Diffusion Language Models for Text Generation. - Minkai Xu; Tomas Geffner; Karsten Kreis; Weili Nie; Yilun Xu; Jure Leskovec; Stefano Ermon; Arash Vahdat (ICLR, 2025)

Intelligent Recognition of Gram-Stained Microscopic Images Based on DIBAS Dataset. - Weili Nie (ISNN, 2025)

A text-guided protein design framework. - Shengchao Liu; Yanjing Li; Zhuoxinran Li; Anthony Gitter; Yutao Zhu 001; Jiarui Lu; Zhao Xu 005; Weili Nie; Arvind Ramanathan; Chaowei Xiao; Jian Tang 005; Hongyu Guo; et al. (Nat. Mac. Intell., 2025)

GenMol: A Drug Discovery Generalist with Discrete Diffusion. - Seul Lee; Karsten Kreis; Srimukh Prasad Veccham; Meng Liu 015; Danny Reidenbach; Yuxing Peng 005; Saee Paliwal; Weili Nie; Arash Vahdat (CoRR, 2025)

A2SB: Audio-to-Audio Schrodinger Bridges. - Zhifeng Kong; Kevin J. Shih; Weili Nie; Arash Vahdat; Sang-gil Lee; João Felipe Santos; Ante Jukic; Rafael Valle; Bryan Catanzaro (CoRR, 2025)

One-step Diffusion Models with f-Divergence Distribution Matching. - Yilun Xu; Weili Nie; Arash Vahdat (CoRR, 2025)