People

Weili Nie
Research Area(s)
Generative AI
Main Field of Interest
Artificial Intelligence and Machine Learning
Google Scholar
https://scholar.google.com/citations?user=zW7BH7oAAAAJ&hl=en&oi=ao

Publications

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
International Conference on Learning Representations (ICLR) 2025
Truncated Consistency Models
Sangyun Lee, Yilun Xu, Tomas Geffner, Giulia Fanti, Karsten Kreis, Arash Vahdat, Weili Nie
International Conference on Learning Representations (ICLR) 2025

2024

Warped Diffusion: Solving Video Inverse Problems with Image Diffusion Models
Giannis Daras, Weili Nie, Karsten Kreis, Alexandros G. Dimakis, Morteza Mardani, Nikola Kovachki, Arash Vahdat
Neural Information Processing Systems (NeurIPS) 2024
Molecule Generation with Fragment Retrieval Augmentation
Seul Lee, Karsten Kreis, Srimukh Prasad Veccham, Meng Liu, Danny Reidenbach, Saee Paliwal, Arash Vahdat, Weili Nie
Neural Information Processing Systems (NeurIPS) 2024
Aligning Target-Aware Molecule Diffusion Models with Exact Energy Optimization
Siyi Gu, Minkai Xu, Alexander Powers, Weili Nie, Tomas Geffner, Karsten Kreis, Jure Leskovec, Arash Vahdat, Stefano Ermon
Neural Information Processing Systems (NeurIPS) 2024

2022

Diffusion Models for Adversarial Purification
Weili Nie, Brandon Guo, Yujia Huang, Chaowei Xiao, Arash Vahdat, Anima Anandkumar
International Conference on Machine Learning (ICML), 2022

2021

Controllable and Compositional Generation with Latent-Space Energy-Based Models
Weili Nie, Arash Vahdat, Anima Anandkumar
Neural Information Processing Systems (NeurIPS) 2021