38 citations · 125 across the 49 of their papers we have counts for
6 papers · 1 filter
NEST: Nested Embedding Representation for Multiscale Clustering
Zhanqi Zhang, Mikio Aoi, Gal Mishne
Real-world data often exhibits cluster structure at multiple resolutions, yet existing methods typically learn a single partition or construct an explicit hierarchy. Inspired by Ma…
Neural Algorithmic Reasoning for Graph Saddle Point Problems
Samantha Chen, Jesse He, Coleman Clougherty +2
Neural algorithmic reasoning, or aligning a neural network with an algorithmic paradigm, has emerged as an approach to solving polynomial-time-solvable and computationally harder c…
Reassessing Muon for Matrix Factorization
Ali Parviz, Gal Mishne, Alex Cloninger
Muon has recently emerged as a strong optimizer for large-scale deep learning, where it reshapes gradient updates through approximate orthogonalization and has been reported to out…
ALIGN: Adversarial Learning for Generalizable Speech Neuroprosthesis
Zhanqi Zhang, Shun Li, Bernardo L. Sabatini +2
Intracortical brain-computer interfaces (BCIs) can decode speech from neural activity with high accuracy when trained on data pooled across recording sessions. In realistic deploym…
MINAR: Mechanistic Interpretability for Neural Algorithmic Reasoning
Jesse He, Helen Jenne, Max Vargas +4
The recent field of neural algorithmic reasoning (NAR) studies the ability of graph neural networks (GNNs) to emulate classical algorithms like Bellman-Ford, a phenomenon known as…
Multi-Integration of Labels across Categories for Component Identification (MILCCI)
Noga Mudrik, Yuxi Chen, Gal Mishne +1
Many fields collect large-scale temporal data through repeated measurements (trials), where each trial is labeled with a set of metadata variables spanning several categories. For…