423 citations · 626 across the 11 of their papers we have counts for
12 papers
PersonaTeaming: Exploring How Introducing Personas Can Improve Automated AI Red-Teaming
Wesley Hanwen Deng, Sunnie S. Y. Kim, Akshita Jha +4
Recent developments in AI governance and safety research have called for red-teaming methods that can effectively surface potential risks posed by AI models. Many of these calls ha…
Disentangled Safety Adapters Enable Efficient Guardrails and Flexible Inference-Time Alignment
Kundan Krishna, Joseph Y Cheng, Charles Maalouf +1
Existing paradigms for ensuring AI safety, such as guardrail models and alignment training, often compromise either inference efficiency or development flexibility. We introduce Di…
Model-based metrics: Sample-efficient estimates of predictive model subpopulation performance
Andrew C. Miller, Leon A. Gatys, Joseph Futoma +1
Machine learning models now commonly developed to screen, diagnose, or predict health conditions are evaluated with a variety of performance metrics. An important first ste…
Modeling patterns of smartphone usage and their relationship to cognitive health
Jonas Rauber, Emily B. Fox, Leon A. Gatys
The ubiquity of smartphone usage in many people's lives make it a rich source of information about a person's mental and cognitive state. In this work we analyze 12 weeks of phone…
Diverse feature visualizations reveal invariances in early layers of deep neural networks
Santiago A. Cadena, Marissa A. Weis, Leon A. Gatys +2
Visualizing features in deep neural networks (DNNs) can help understanding their computations. Many previous studies aimed to visualize the selectivity of individual units by findi…
Guiding human gaze with convolutional neural networks
Leon A. Gatys, Matthias Kümmerer, Thomas S. A. Wallis +1
The eye fixation patterns of human observers are a fundamental indicator of the aspects of an image to which humans attend. Thus, manipulating fixation patterns to guide human atte…
Synthesising Dynamic Textures using Convolutional Neural Networks
Christina M. Funke, Leon A. Gatys, Alexander S. Ecker +1
Here we present a parametric model for dynamic textures. The model is based on spatiotemporal summary statistics computed from the feature representations of a Convolutional Neural…
Controlling Perceptual Factors in Neural Style Transfer
Leon A. Gatys, Alexander S. Ecker, Matthias Bethge +2
Neural Style Transfer has shown very exciting results enabling new forms of image manipulation. Here we extend the existing method to introduce control over spatial location, colou…
Preserving Color in Neural Artistic Style Transfer
Leon A. Gatys, Matthias Bethge, Aaron Hertzmann +1
This note presents an extension to the neural artistic style transfer algorithm (Gatys et al.). The original algorithm transforms an image to have the style of another given image.…
Texture Synthesis Using Shallow Convolutional Networks with Random Filters
Ivan Ustyuzhaninov, Wieland Brendel, Leon A. Gatys +1
Here we demonstrate that the feature space of random shallow convolutional neural networks (CNNs) can serve as a surprisingly good model of natural textures. Patches from the same…
A Neural Algorithm of Artistic Style
Leon A. Gatys, Alexander S. Ecker, Matthias Bethge
In fine art, especially painting, humans have mastered the skill to create unique visual experiences through composing a complex interplay between the content and style of an image…
Texture Synthesis Using Convolutional Neural Networks
Leon A. Gatys, Alexander S. Ecker, Matthias Bethge
Here we introduce a new model of natural textures based on the feature spaces of convolutional neural networks optimised for object recognition. Samples from the model are of high…