Zobrazeno 1 - 10
of 2 985
pro vyhledávání: '"Young, Stephen A."'
Autor:
Brown, Samuel B., Young, Stephen, Wagenknecht, Adam, Jakubisin, Daniel, Thornton, Charles E., Orndorff, Aaron, Headley, William C.
Denoising autoencoders for signal processing applications have been shown to experience significant difficulty in learning to reconstruct radio frequency communication signals, particularly in the large sample regime. In communication systems, this c
Externí odkaz:
http://arxiv.org/abs/2410.03423
Fine-tuning Protein Language Models with Deep Mutational Scanning improves Variant Effect Prediction
Autor:
Lafita, Aleix, Gonzalez, Ferran, Hossam, Mahmoud, Smyth, Paul, Deasy, Jacob, Allyn-Feuer, Ari, Seaton, Daniel, Young, Stephen
Protein Language Models (PLMs) have emerged as performant and scalable tools for predicting the functional impact and clinical significance of protein-coding variants, but they still lag experimental accuracy. Here, we present a novel fine-tuning app
Externí odkaz:
http://arxiv.org/abs/2405.06729
In data science, hypergraphs are natural models for data exhibiting multi-way relations, whereas graphs only capture pairwise. Nonetheless, many proposed hypergraph neural networks effectively reduce hypergraphs to undirected graphs via symmetrized m
Externí odkaz:
http://arxiv.org/abs/2402.09676
Autor:
Shivakumar, Shruti, Amburg, Ilya, Aksoy, Sinan G., Li, Jiajia, Young, Stephen J., Aluru, Srinivas
Hypergraphs are a popular paradigm to represent complex real-world networks exhibiting multi-way relationships of varying sizes. Mining centrality in hypergraphs via symmetric adjacency tensors has only recently become computationally feasible for la
Externí odkaz:
http://arxiv.org/abs/2311.08595
Autor:
Kay, Bill, Aksoy, Sinan G., Baird, Molly, Best, Daniel M., Jenne, Helen, Joslyn, Cliff, Potvin, Christopher, Henselman-Petrusek, Gregory, Seppala, Garret, Young, Stephen J., Purvine, Emilie
In this position paper, we argue that when hypergraphs are used to capture multi-way local relations of data, their resulting topological features describe global behaviour. Consequently, these features capture complex correlations that can then serv
Externí odkaz:
http://arxiv.org/abs/2312.00023
Autor:
Myers, Audun, Bittner, Alyson, Aksoy, Sinan, Best, Daniel M., Henselman-Petrusek, Gregory, Jenne, Helen, Joslyn, Cliff, Kay, Bill, Seppala, Garret, Young, Stephen J., Purvine, Emilie
In this study we synthesize zigzag persistence from topological data analysis with autoencoder-based approaches to detect malicious cyber activity and derive analytic insights. Cybersecurity aims to safeguard computers, networks, and servers from var
Externí odkaz:
http://arxiv.org/abs/2309.08010
Sequence modelling approaches for epigenetic profile prediction have recently expanded in terms of sequence length, model size, and profile diversity. However, current models cannot infer on many experimentally feasible tissue and assay pairs due to
Externí odkaz:
http://arxiv.org/abs/2308.11671
While multilinear algebra appears natural for studying the multiway interactions modeled by hypergraphs, tensor methods for general hypergraphs have been stymied by theoretical and practical barriers. A recently proposed adjacency tensor is applicabl
Externí odkaz:
http://arxiv.org/abs/2306.17825
Autor:
Aksoy, Sinan G., Bennink, Ryan, Chen, Yuzhou, Frías, José, Gel, Yulia R., Kay, Bill, Naumann, Uwe, Marrero, Carlos Ortiz, Petyuk, Anthony V., Roy, Sandip, Segovia-Dominguez, Ignacio, Veldt, Nate, Young, Stephen J.
We present and discuss seven different open problems in applied combinatorics. The application areas relevant to this compilation include quantum computing, algorithmic differentiation, topological data analysis, iterative methods, hypergraph cut alg
Externí odkaz:
http://arxiv.org/abs/2303.11464
Autor:
Young, Stephen M.1 (AUTHOR) Stephen.young@otago.ac.nz
Publikováno v:
Law & Humanities. Oct2024, p1-22. 22p.
