2 citations · 3 across the 4 of their papers we have counts for
4 papers
BRIDLE: Generalized Self-supervised Learning with Quantization
Hoang M. Nguyen, Satya N. Shukla, Qiang Zhang +6
Self-supervised learning has been a powerful approach for learning meaningful representations from unlabeled data across various domains, reducing the reliance on large labeled dat…
Intriguing Differences Between Zero-Shot and Systematic Evaluations of Vision-Language Transformer Models
Shaeke Salman, Md Montasir Bin Shams, Xiuwen Liu +1
Transformer-based models have dominated natural language processing and other areas in the last few years due to their superior (zero-shot) performance on benchmark datasets. Howev…
Convergence Analysis for General Probability Flow ODEs of Diffusion Models in Wasserstein Distances
Xuefeng Gao, Lingjiong Zhu
Score-based generative modeling with probability flow ordinary differential equations (ODEs) has achieved remarkable success in a variety of applications. While various fast ODE-ba…
Wasserstein Convergence Guarantees for a General Class of Score-Based Generative Models
Xuefeng Gao, Hoang M. Nguyen, Lingjiong Zhu
Score-based generative models (SGMs) is a recent class of deep generative models with state-of-the-art performance in many applications. In this paper, we establish convergence gua…