Search Results for author:
Found 7 papers, 6 papers with code
$O(k)$-Equivariant Dimensionality Reduction on Stiefel Manifolds
Then, we define a continuous and $O(k)$-equivariant map $\pi_\alpha$ that acts as a ``closest point operator'' to project the data onto the image of $V_k(\mathbb{R}^n)$ in $V_k(\mathbb{R}^N)$ under the embedding determined by $\alpha$, while minimizing distortion.
Predicting the Future of AI with AI: High-quality link prediction in an exponentially growing knowledge network
For that, we use more than 100, 000 research papers and build up a knowledge network with more than 64, 000 concept nodes.
Distilled Non-Semantic Speech Embeddings with Binary Neural Networks for Low-Resource Devices
This work introduces BRILLsson, a novel binary neural network-based representation learning model for a broad range of non-semantic speech tasks.
Automatic Sleep Scoring from Large-scale Multi-channel Pediatric EEG
But pediatric sleep is severely under-researched compared to adult sleep in the context of machine learning for health, and sleep scoring algorithms developed for adults usually perform poorly on infants.
Joint Content-Context Analysis of Scientific Publications: Identifying Opportunities for Collaboration in Cognitive Science
This work studies publications in the field of cognitive science and utilizes mathematical techniques to connect the analysis of the papers' content (abstracts) to the context (citation, journals).
A Large Collection of Real-world Pediatric Sleep Studies
Despite being crucial to health and quality of life, sleep -- especially pediatric sleep -- is not yet well understood.
Vector-Valued Graph Trend Filtering with Non-Convex Penalties
This work studies the denoising of piecewise smooth graph signals that exhibit inhomogeneous levels of smoothness over a graph, where the value at each node can be vector-valued.
