6 citations · 25 across the 41 of their papers we have counts for
11 papers · 1 filter
Haldane Bundles: A Dataset for Learning to Predict the Chern Number of Line Bundles on the Torus
Cody Tipton, Elizabeth Coda, Davis Brown +5
Characteristic classes, which are abstract topological invariants associated with vector bundles, have become an important notion in modern physics with surprising real-world conse…
Understanding the Inner Workings of Language Models Through Representation Dissimilarity
Davis Brown, Charles Godfrey, Nicholas Konz +2
As language models are applied to an increasing number of real-world applications, understanding their inner workings has become an important issue in model trust, interpretability…
Attributing Learned Concepts in Neural Networks to Training Data
Nicholas Konz, Charles Godfrey, Madelyn Shapiro +3
By now there is substantial evidence that deep learning models learn certain human-interpretable features as part of their internal representations of data. As having the right (or…
ICML 2023 Topological Deep Learning Challenge : Design and Results
Mathilde Papillon, Mustafa Hajij, Helen Jenne +53
This paper presents the computational challenge on topological deep learning that was hosted within the ICML 2023 Workshop on Topology and Geometry in Machine Learning. The competi…
SCITUNE: Aligning Large Language Models with Human-Curated Scientific Multimodal Instructions
Sameera Horawalavithana, Sai Munikoti, Ian Stewart +2
Instruction finetuning is a popular paradigm to align large language models (LLM) with human intent. Despite its popularity, this idea is less explored in improving LLMs to align e…
ColMix -- A Simple Data Augmentation Framework to Improve Object Detector Performance and Robustness in Aerial Images
Cuong Ly, Grayson Jorgenson, Dan Rosa de Jesus +3
In the last decade, Convolutional Neural Network (CNN) and transformer based object detectors have achieved high performance on a large variety of datasets. Though the majority of…
How many dimensions are required to find an adversarial example?
Charles Godfrey, Henry Kvinge, Elise Bishoff +4
Past work exploring adversarial vulnerability have focused on situations where an adversary can perturb all dimensions of model input. On the other hand, a range of recent works co…
Fast computation of permutation equivariant layers with the partition algebra
Charles Godfrey, Michael G. Rawson, Davis Brown +1
Linear neural network layers that are either equivariant or invariant to permutations of their inputs form core building blocks of modern deep learning architectures. Examples incl…
Edit at your own risk: evaluating the robustness of edited models to distribution shifts
Davis Brown, Charles Godfrey, Cody Nizinski +2
The current trend toward ever-larger models makes standard retraining procedures an ever-more expensive burden. For this reason, there is growing interest in model editing, which e…
Exploring the Representation Manifolds of Stable Diffusion Through the Lens of Intrinsic Dimension
Henry Kvinge, Davis Brown, Charles Godfrey
Prompting has become an important mechanism by which users can more effectively interact with many flavors of foundation model. Indeed, the last several years have shown that well-…
Parameters, Properties, and Process: Conditional Neural Generation of Realistic SEM Imagery Towards ML-assisted Advanced Manufacturing
Scott Howland, Lara Kassab, Keerti Kappagantula +2
The research and development cycle of advanced manufacturing processes traditionally requires a large investment of time and resources. Experiments can be expensive and are hence c…