Authors: Marc Chalé, Nathaniel D. Bastian, Jeffery Weir
arXiv
The number of cyber threats against both wired and wireless computer systems and other components of the Internet of Things continues to increase annually. In this work, an algorithm selection framewo...
Authors: Trevor Hefley
arXiv
Researchers and managers model ecological communities to infer the biotic and abiotic variables that shape species' ranges, habitat use, and co-occurrence which, in turn, are used to support managemen...
Authors: Edgar Santos-Fernandez, Erin E. Peterson, Julie Vercelloni, Em Rushworth, Kerrie Mengersen
arXiv
Many research domains use data elicited from "citizen scientists" when a direct measure of a process is expensive or infeasible. However, participants may report incorrect estimates or classifications...
Authors: Sarod Yatawatta
arXiv
Mitigation of radio frequency interference (RFI) is essential to deliver science-ready radio interferometric data to astronomers. In this paper, using dual polarized radio interferometers, we propose...
Authors: Guanyu Hu, Zhihua Ma, Insu Paek
arXiv
Item response theory (IRT) is a popular modeling paradigm for measuring subject latent traits and item properties according to discrete responses in tests or questionnaires. There are very limited dis...
Authors: Navid Alemi Koohbanani, Mostafa Jahanifar, Neda Zamani Tajadin, Nasir Rajpoot
arXiv
Object segmentation is an important step in the workflow of computational pathology. Deep learning based models generally require large amount of labeled data for precise and reliable prediction. Howe...
Authors: Andres Babino, Marcelo O. Magnasco
arXiv
During the COVID-19 pandemic, the scientific community developed predictive models to evaluate potential governmental interventions. However, the analysis of the effects these interventions had is les...
Authors: Tianjian Zhou, Yuan Ji
arXiv
The outbreak of Coronavirus Disease 2019 (COVID-19) is an ongoing pandemic affecting over 200 countries and regions. Inference about the transmission dynamics of COVID-19 can provide important insight...
Authors: Lukas Muttenthaler, Nora Hollenstein, Maria Barrett
arXiv
Cognitively inspired NLP leverages human-derived data to teach machines about language processing mechanisms. Recently, neural networks have been augmented with behavioral data to solve a range of NLP...
Authors: Irina Blazhievska
arXiv
Thesis is devoted to the application of cumulant analysis in the estimation of impulse response functions for continuous time-invariant linear systems, including systems with inner noises. The main as...
Authors: Joseph Paul Cohen, Lan Dao, Paul Morrison, Karsten Roth, Yoshua Bengio, Beiyi Shen, Almas Abbasi, Mahsa Hoshmand-Kochi, Marzyeh Ghassemi, Haifang Li, Tim Q Duong
arXiv
Purpose: The need to streamline patient management for COVID-19 has become more pressing than ever. Chest X-rays provide a non-invasive (potentially bedside) tool to monitor the progression of the dis...
Authors: Yanshuai Tu, Duyan Ta, Zhong-Lin Lu, Yalin Wang
arXiv
The mapping between the visual input on the retina to the cortical surface, i.e., retinotopic mapping, is an important topic in vision science and neuroscience. Human retinotopic mapping can be reveal...
Authors: Roberto Baviera, Giuseppe Messuti
arXiv
Probabilistic forecasting of power consumption in a middle-term horizon (months to a year) is a main challenge in the energy sector. It plays a key role in planning future generation plants and transm...
Authors: Zachary Wojtowicz, Simon DeDeo
arXiv
Recent work in cognitive science has uncovered a diversity of explanatory values, or dimensions along which we judge explanations as better or worse. We propose a Bayesian account of how these values...
Authors: Kei Hirose
arXiv
We consider the problem of short- and medium-term electricity load forecasting by using past loads and daily weather forecast information. Conventionally, many researchers have directly applied regres...