1 code implementation • 19 Sep 2023 • Andrew Lee, Harlin Lee, Jose A. Perea, Nikolas Schonsheck, Madeleine Weinstein
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.
2 code implementations • 23 Sep 2022 • Mario Krenn, Lorenzo Buffoni, Bruno Coutinho, Sagi Eppel, Jacob Gates Foster, Andrew Gritsevskiy, Harlin Lee, Yichao Lu, Joao P. Moutinho, Nima Sanjabi, Rishi Sonthalia, Ngoc Mai Tran, Francisco Valente, Yangxinyu Xie, Rose Yu, Michael Kopp
For that, we use more than 100, 000 research papers and build up a knowledge network with more than 64, 000 concept nodes.
1 code implementation • 12 Jul 2022 • Harlin Lee, Aaqib Saeed
This work introduces BRILLsson, a novel binary neural network-based representation learning model for a broad range of non-semantic speech tasks.
1 code implementation • 30 Jun 2022 • Harlin Lee, Aaqib Saeed
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.
no code implementations • NeurIPS Workshop AI4Scien 2021 • Lu Cheng, Girish Ganesan, William He, Daniel Silverston, Harlin Lee, Jacob Gates Foster
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).
1 code implementation • 26 Feb 2021 • Harlin Lee, Boyue Li, Shelly DeForte, Mark Splaingard, Yungui Huang, Yuejie Chi, Simon Lin Linwood
Despite being crucial to health and quality of life, sleep -- especially pediatric sleep -- is not yet well understood.
1 code implementation • 29 May 2019 • Rohan Varma, Harlin Lee, Jelena Kovačević, Yuejie Chi
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.