Authors: David Banks, Víctor Gallego, Roi Naveiro, David Ríos Insua
arXiv
Adversarial risk analysis (ARA) is a relatively new area of research that informs decision-making when facing intelligent opponents and uncertain outcomes. It enables an analyst to express her Bayesia...
Authors: Yun Zhao, Richard Jiang, Zhenni Xu, Elmer Guzman, Paul K. Hansma, Linda Petzold
arXiv
Multi-electrode arrays (MEAs) can record extracellular action potentials (also known as 'spikes') from hundreds or thousands of neurons simultaneously. Inference of a functional network from a spike t...
Authors: Chandramouli Kamanchi, Gopinath Ashok Kumar, Nachiappan Sundaram, Ravindra Babu T, Chaithanya Bandi
arXiv
We describe a supply chain optimization model deployed in an online fashion e-commerce company in India called Myntra. Our model is simple, elegant and easy to put into service. The model utilizes his...
Authors: Mirko Fiacchini, Mazen Alamir
arXiv
This paper presents a data-based simple model for fitting the available data of the Covid-19 pandemic evolution in France. The time series concerning the 13 regions of mainland France have been consid...
Authors: Anne Draelos, Eva A. Naumann, John M. Pearson
arXiv
One of the primary goals of systems neuroscience is to relate the structure of neural circuits to their function, yet patterns of connectivity are difficult to establish when recording from large popu...
Authors: Raphaëlle Momal, Stéphane Robin, Christophe Ambroise
arXiv
Network inference aims at unraveling the dependency structure relating jointly observed variables. Graphical models provide a general framework to distinguish between marginal and conditional dependen...
Authors: Michael J. Grayling, Adrian P. Mander
arXiv
Purpose: Two-stage single-arm trial designs are commonly used in phase II oncology to infer treatment effects for a binary primary outcome (e.g., tumour response). It is imperative that such studies b...
Authors: Brian Lucena
arXiv
Gradient boosting methods based on Structured Categorical Decision Trees (SCDT) have been demonstrated to outperform numerical and one-hot-encodings on problems where the categorical variable has a kn...
Authors: Shashank Kumbhare, Amir Shahmoradi
arXiv
Markov Chain Monte Carlo (MCMC) algorithms are widely used for stochastic optimization, sampling, and integration of mathematical objective functions, in particular, in the context of Bayesian inverse...
Authors: Eren Kurshan, Hongda Shen, Jiahao Chen
arXiv
AI systems have found a wide range of application areas in financial services. Their involvement in broader and increasingly critical decisions has escalated the need for compliance and effective mode...
Authors: Xiaona Xia
arXiv
Group tendency is a research branch of computer assisted learning. The construction of good learning behavior is of great significance to learners' learning process and learning effect, and is the key...
Authors: Niccolò Dalmasso, Galen Vincent, Dorit Hammerling, Ann B. Lee
arXiv
Climate models play a crucial role in understanding the effect of environmental and man-made changes on climate to help mitigate climate risks and inform governmental decisions. Large global climate m...
Authors: Chaoqing Xu, Guodao Sun, Ronghua Liang, Xiufang Xu
arXiv
Brain fiber tracts are widely used in studying brain diseases, which may lead to a better understanding of how disease affects the brain. The segmentation of brain fiber tracts assumed enormous import...
Authors: Alex Diana, Eleni Matechou, Jim Griffin, Todd Arnold, Richard Griffiths, John Pickering, Simone Tenan, Stefano Volponi
arXiv
Wildlife monitoring for open populations can be performed using a number of different survey methods. Each survey method gives rise to a type of data and, in the last five decades, a large number of a...
Authors: Sayani Gupta, Puneet Chitkara
arXiv
Day Ahead Electricity Markets (DAMs) in India are thin but growing. Consistent price forecasts are important for their utilization in portfolio optimization models. Univariate or multivariate models w...