6 citations · 25 across the 41 of their papers we have counts for
7 papers · 1 filter
Saddle-Free Guidance: Improved On-Manifold Sampling without Labels or Additional Training
Eric Yeats, Darryl Hannan, Wilson Fearn +3
Score-based generative models require guidance in order to generate plausible, on-manifold samples. The most popular guidance method, Classifier-Free Guidance (CFG), is only applic…
Even with AI, Bijection Discovery is Still Hard: The Opportunities and Challenges of OpenEvolve for Novel Bijection Construction
Davis Brown, Jesse He, Helen Jenne +2
Evolutionary program synthesis systems such as AlphaEvolve, OpenEvolve, and ShinkaEvolve offer a new approach to AI-assisted mathematical discovery. These systems utilize teams of…
A Connection Between Score Matching and Local Intrinsic Dimension
Eric Yeats, Aaron Jacobson, Darryl Hannan +4
The local intrinsic dimension (LID) of data is a fundamental quantity in signal processing and learning theory, but quantifying the LID of high-dimensional, complex data has been a…
Automating Evaluation of Diffusion Model Unlearning with (Vision-) Language Model World Knowledge
Eric Yeats, Darryl Hannan, Henry Kvinge +2
Machine unlearning (MU) is a promising cost-effective method to cleanse undesired information (generated concepts, biases, or patterns) from foundational diffusion models. While MU…
FMG-Det: Foundation Model Guided Robust Object Detection
Darryl Hannan, Timothy Doster, Henry Kvinge +2
Collecting high quality data for object detection tasks is challenging due to the inherent subjectivity in labeling the boundaries of an object. This makes it difficult to not only…
Foundation Models for Remote Sensing: An Analysis of MLLMs for Object Localization
Darryl Hannan, John Cooper, Dylan White +3
Multimodal large language models (MLLMs) have altered the landscape of computer vision, obtaining impressive results across a wide range of tasks, especially in zero-shot settings.…
Machine Learning meets Algebraic Combinatorics: A Suite of Datasets Capturing Research-level Conjecturing Ability in Pure Mathematics
Herman Chau, Helen Jenne, Davis Brown +4
With recent dramatic increases in AI system capabilities, there has been growing interest in utilizing machine learning for reasoning-heavy, quantitative tasks, particularly mathem…