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09/10/2023
SA-Solver: Stochastic Adams Solver for Fast Sampling of Diffusion Models
Diffusion Probabilistic Models (DPMs) have achieved considerable success...
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07/10/2023
Enhancing Adversarial Robustness via Score-Based Optimization
Adversarial attacks have the potential to mislead deep neural network cl...
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07/04/2023
Training Energy-Based Models with Diffusion Contrastive Divergences
Energy-Based Models (EBMs) have been widely used for generative modeling...
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06/08/2023
Entropy-based Training Methods for Scalable Neural Implicit Sampler
Efficiently sampling from un-normalized target distributions is a fundam...
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05/29/2023
Diff-Instruct: A Universal Approach for Transferring Knowledge From Pre-trained Diffusion Models
Due to the ease of training, ability to scale, and high sample quality, ...
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04/09/2023
A Comprehensive Survey on Knowledge Distillation of Diffusion Models
Diffusion Models (DMs), also referred to as score-based diffusion models...
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02/03/2023
A Lipschitz Bandits Approach for Continuous Hyperparameter Optimization
One of the most critical problems in machine learning is HyperParameter ...
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01/03/2021
Binary Outcome Copula Regression Model with Sampling Gradient Fitting
Use copula to model dependency of variable extends multivariate gaussian...
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09/22/2020
