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Found 6 papers, 2 papers with code
Vote'n'Rank: Revision of Benchmarking with Social Choice Theory
The development of state-of-the-art systems in different applied areas of machine learning (ML) is driven by benchmarks, which have shaped the paradigm of evaluating generalisation capabilities from multiple perspectives.
An Optimal Transport Perspective on Unpaired Image Super-Resolution
First, the learned SR map is always an optimal transport (OT) map.
A Differentiable Language Model Adversarial Attack on Text Classifiers
Moreover, due to the usage of the fine-tuned language model, the generated adversarial examples are hard to detect, thus current models are not robust.
Gradient-based adversarial attacks on categorical sequence models via traversing an embedded world
The first approach adopts a Monte-Carlo method and allows usage in any scenario, the second approach uses a continuous relaxation of models and target metrics, and thus allows usage of state-of-the-art methods for adversarial attacks with little additional effort.
Latent-Space Laplacian Pyramids for Adversarial Representation Learning with 3D Point Clouds
Constructing high-quality generative models for 3D shapes is a fundamental task in computer vision with diverse applications in geometry processing, engineering, and design.
Data Science with Vadalog: Bridging Machine Learning and Reasoning
Following the recent successful examples of large technology companies, many modern enterprises seek to build knowledge graphs to provide a unified view of corporate knowledge and to draw deep insights using machine learning and logical reasoning.
