3 citations · 4 across the 8 of their papers we have counts for
10 papers
QuanVI: Score-based Variational Inference via Quantum Maximally Mixed States
Yuchen Cong, Zerui Tao, Chao Li +2
Score-based variational inference (VI) provides an alternative to Kullback--Leibler (KL)-based VI by minimizing the Fisher divergence between the variational distribution and the t…
Bayesian Tensor Decomposition with Diffusion Model Prior
Zerui Tao, Qibin Zhao
Low-rank tensor decomposition (TD) is usually effective on clean, fully observed data, but it often degrades under severe missingness or noise. Low-rankness is itself a useful but…
On the Approximation Complexity of Matrix Product Operator (MPO) Born Machines
Chao Li, Zerui Tao, Yuchen Cong +2
Matrix product operator Born machines (MPO-BMs) are tractable tensor-network models for probabilistic modeling, yet their approximation capabilities remain poorly understood in the…
Calibrating Uncertainty for Zero-Shot Adversarial CLIP
Wenjing Lu, Zerui Tao, Yuning Qiu +3
CLIP delivers strong zero-shot classification but remains highly vulnerable to adversarial attacks. Prior adversarial fine-tuning work primarily matches predicted logits between cl…
Model-Free Adversarial Purification via Coarse-To-Fine Tensor Network Representation
Guang Lin, Duc Thien Nguyen, Zerui Tao +3
Deep neural networks are known to be vulnerable to well-designed adversarial attacks. Although numerous defense strategies have been proposed, many are tailored to the specific att…
Transformed Low-rank Adaptation via Tensor Decomposition and Its Applications to Text-to-image Models
Zerui Tao, Yuhta Takida, Naoki Murata +2
Parameter-Efficient Fine-Tuning (PEFT) of text-to-image models has become an increasingly popular technique with many applications. Among the various PEFT methods, Low-Rank Adaptat…
Scalable Bayesian Tensor Ring Factorization for Multiway Data Analysis
Zerui Tao, Toshihisa Tanaka, Qibin Zhao
Tensor decompositions play a crucial role in numerous applications related to multi-way data analysis. By employing a Bayesian framework with sparsity-inducing priors, Bayesian Ten…
Adversarial Guided Diffusion Models for Adversarial Purification
Guang Lin, Zerui Tao, Jianhai Zhang +2
Diffusion model (DM) based adversarial purification (AP) has proven to be a powerful defense method that can remove adversarial perturbations and generate a purified example withou…
Efficient Nonparametric Tensor Decomposition for Binary and Count Data
Zerui Tao, Toshihisa Tanaka, Qibin Zhao
In numerous applications, binary reactions or event counts are observed and stored within high-order tensors. Tensor decompositions (TDs) serve as a powerful tool to handle such hi…
Permutation Search of Tensor Network Structures via Local Sampling
Chao Li, Junhua Zeng, Zerui Tao +1
Recent works put much effort into tensor network structure search (TN-SS), aiming to select suitable tensor network (TN) structures, involving the TN-ranks, formats, and so on, for…