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Found 4 papers, 1 papers with code
Structure-Preserving Network Compression Via Low-Rank Induced Training Through Linear Layers Composition
Deep Neural Networks (DNNs) have achieved remarkable success in addressing many previously unsolvable tasks.
Decoupled Data Consistency with Diffusion Purification for Image Restoration
To solve image restoration problems, many existing techniques achieve data consistency by incorporating additional likelihood gradient steps into the reverse sampling process of diffusion models.
A Differentiable Approach to Combinatorial Optimization using Dataless Neural Networks
In particular, we reduce the combinatorial optimization problem to a neural network and employ a dataless training scheme to refine the parameters of the network such that those parameters yield the structure of interest.
BOSS: Bidirectional One-Shot Synthesis of Adversarial Examples
To this end, we present a problem that encodes objectives on the distance between the desired and output distributions of the trained model and the similarity between such inputs and the synthesized examples.
