4 papers · 1 filter
Representation Collapsing Problems in Vector Quantization
Wenhao Zhao, Qiran Zou, Rushi Shah +1
Vector quantization is a technique in machine learning that discretizes continuous representations into a set of discrete vectors. It is widely employed in tokenizing data represen…
Gaussian Mixture Vector Quantization with Aggregated Categorical Posterior
Mingyuan Yan, Jiawei Wu, Rushi Shah +1
The vector quantization is a widely used method to map continuous representation to discrete space and has important application in tokenization for generative mode, bottlenecking…
Improving Discrete Optimisation Via Decoupled Straight-Through Estimator
Rushi Shah, Mingyuan Yan, Michael Curtis Mozer +1
The Straight-Through Estimator (STE) is the dominant method for training neural networks with discrete variables, enabling gradient-based optimisation by routing gradients through…
VQSynery: Robust Drug Synergy Prediction With Vector Quantization Mechanism
Jiawei Wu, Mingyuan Yan, Dianbo Liu
The pursuit of optimizing cancer therapies is significantly advanced by the accurate prediction of drug synergy. Traditional methods, such as clinical trials, are reliable yet encu…