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Razvan Veliche

Publications and source records attributed to Razvan Veliche.

8 recordsLinked to original sources
arXiv2023

SICO: Simulation for Infection Control Operations

In response to the COVID-19 pandemic and the potential threat of future epidemics caused by novel viruses, we developed a flexible framework for modeling disease intervention effects. This tool is intended to aid decision makers at multiple levels as they compare possible responses to emerging epidemiological threats for optimal control and reduction of harm. The framework is specifically designed to be both scalable and modular, allowing it to model a variety of population levels, viruses, testing methods and strategies--including pooled testing--and intervention strategies. In this paper, we provide an overview of this framework and examine the impact of different intervention strategies and their impact on infection dynamics.

cs.MA↗
arXiv2023

Representational Tenets for Memory Athletics

We describe the current state of world-class memory competitions, including the methods used to prepare for and compete in memory competitions, based on the subjective report of World Memory Championship Grandmaster and co-author Nelson Dellis. We then explore the reported experiences through the lens of the Simulated, Situated, and Structurally coherent Qualia (S3Q) theory of consciousness, in order to propose a set of experiments to help further understand the boundaries of expert memory performance.

q-bio.NC↗
arXiv2022

Static Seeding and Clustering of LSTM Embeddings to Learn from Loosely Time-Decoupled Events

Humans learn from the occurrence of events in a different place and time to predict similar trajectories of events. We define Loosely Decoupled Timeseries (LDT) phenomena as two or more events that could happen in different places and across different timelines but share similarities in the nature of the event and the properties of the location. In this work we improve on the use of Recurring Neural Networks (RNN), in particular Long Short-Term Memory (LSTM) networks, to enable AI solutions that generate better timeseries predictions for LDT. We use similarity measures between timeseries based on the trends and introduce embeddings representing those trends. The embeddings represent properties of the event which, coupled with the LSTM structure, can be clustered to identify similar temporally unaligned events. In this paper, we explore methods of seeding a multivariate LSTM from time-invariant data related to the geophysical and demographic phenomena being modeled by the LSTM. We apply these methods on the timeseries data derived from the COVID-19 detected infection and death cases. We use publicly available socio-economic data to seed the LSTM models, creating embeddings, to determine whether such seeding improves case predictions. The embeddings produced by these LSTMs are clustered to identify best-matching candidates for forecasting an evolving timeseries. Applying this method, we show an improvement in 10-day moving average predictions of disease propagation at the US County level.

cs.LG↗
arXiv2006

Maximally symmetric stable curves II

We find a sharp bound for the order of the automorphism group of a stable curve of genus $g$ with $3g-3$ nodes, and a sharp bound for the order of the automorphism group of such a curve with all smooth components. Combined with the results of our article math.CO/0608645 we find that graph theoretically, the cubic graph with a given number of vertices and most automorphisms is simple, but algebro-geometrically, the stable curves with $3g-3$ nodes that have the most automorphisms have non-simple dual graph.

math.AG↗
arXiv2006

Cubic graphs with most automorphisms

We give a sharp bound for the automorphism group of a cubic simple graph with a given number of vertices. For each number of vertices we give an explicit graph attaining the bound, and prove its uniqueness in special cases.

math.CO↗
arXiv2006

Maximally symmetric stable curves

We give a sharp bound on the number of automorphisms of a stable curve of a given genus and describe all curves attaining this bound.

math.AG↗
arXiv2006

Variation of hyperplane sections

A result of Beauville states that with a few positive characterstic exceptions, the smooth hyperplane sections of hypersurfaces of degree $d>2$ in projective space are not all isomorphic. We address the question of whether these sections vary as much as possible. In arbitrary characteristic, we show that this is the case for a general hypersurface.

math.AG↗