Optimal dividends for insurers with climate tipping point consideration.
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Much research has been conducted arguing that tipping points at which complex systems experience phase transitions are difficult to identify. To test the existence of tipping points in financial markets, based on the alternating offer strategic model we propose a network of bargaining agents who mutually either coopera…
Framework detects tipping points in complex systems using ML.
CNMs detect tipping points in complex systems using causal network markers.
A new method identifies critical transitions in high-dimensional data.
Model shows wealth taxes can cause sudden emigration waves, impacting GDP.
The cost-benefit analysis formulates the holy trinity of objectives of project management - cost, schedule, and benefits. As our previous research has shown, ICT projects deviate from their initial cost estimate by more than 10% in 8 out of 10 cases. Academic research has argued that Optimism Bias and Black Swan Blindn…
Machine learning detects tipping points in complex systems.
We study the phenomenon of Type-II curvature blow-up in mean curvature flows of rotationally symmetric noncompact embedded hypersurfaces. Using analytic techniques based on formal matched asymptotics and the construction of upper and lower barrier solutions enveloping formal solutions with prescribed behavior, we show …
We continue the study, initiated by the first two authors in \cite{IW19}, of Type-II curvature blow-up in mean curvature flow of complete noncompact embedded hypersurfaces. In particular, we construct mean curvature flow solutions, in the rotationally symmetric class, with the following precise asymptotics near the "va…
In this paper, we study the precise asymptotics of noncompact Type-IIb solutions to the mean curvature flow. Precisely, for each real number , we construct mean curvature flow solutions, in the rotationally symmetric class, with the following precise asymptotics as : (1) The highest curvature conc…
Facial Key Points (FKPs) Detection is an important and challenging problem in the fields of computer vision and machine learning. It involves predicting the co-ordinates of the FKPs, e.g. nose tip, center of eyes, etc, for a given face. In this paper, we propose a LeNet adapted Deep CNN model - NaimishNet, to operate o…
Novel approach detects early warning indicators in complex systems.
Minimal TIP and TIF found in compact spacetimes, impacting spacetime splitting.
TIP-Search optimizes market prediction accuracy and timeliness under uncertain load.
Framework for analyzing dynamic topological changes in point clouds using persistent homology and dynamic optimal transport.
This paper proposes a general model for synchronized crowding behavior. An order parameter is introduced to quantify the level of synchronization which is shown a function of percentage of agents in reactive state. Further, synchronization is shown to be driven by the most active agents with the highest volatility. A t…
Gradient estimate for linearized translator equation in R^4.
Numerical simulations show stability of Type-II singularities in noncompact hypersurfaces.
Let be a surface with Riemannian metric and curved conic singularities. More precisely, a neighbourhood of a singularity is isometric to with metric . We study the spectral geometry of using the heat trace expansion. We express the first few…
The use of drug combinations often leads to polypharmacy side effects (POSE). A recent method formulates POSE prediction as a link prediction problem on a graph of drugs and proteins, and solves it with Graph Convolutional Networks (GCNs). However, due to the complex relationships in POSE, this method has high computat…
In this short article, we prove the existence of ancient solutions of the mean curvature flow that for t -> 0 collapse to a round point, but for t -> -infinity become more and more oval: near the center they have asymptotic shrinkers modeled on round cylinders S^j x R^n-j and near the tips they have asymptotic translat…
Geometrically interpolates rigid body motions with initial and terminal twists.
ACI identifies cause-effect relationships and causal influence ranges in dynamical systems.
The aim of this work is to explore the possible types of phenomena that simple macroeconomic Agent-Based models (ABM) can reproduce. We propose a methodology, inspired by statistical physics, that characterizes a model through its 'phase diagram' in the space of parameters. Our first motivation is to understand the lar…
TDA detects financial bubbles through early warning signals.
Study on heat equation and eigenfunctions on RCD spaces, proving unique continuation.
Study quantifies firm risks from nature decline, showing significant equity losses.
Paper proves unique tangent flow at infinity for entropy-limited curve shortening.
To achieve the ambitious aims of the Paris climate agreement, the majority of fossil-fuel reserves needs to remain underground. As current national government commitments to mitigate greenhouse gas emissions are insufficient by far, actors such as institutional and private investors and the social movement on divestmen…
Paper proposes a method to encrypt faces while maintaining visual similarity.
Many biological characteristics of evolutionary interest are not scalar variables but continuous functions. Here we use phylogenetic Gaussian process regression to model the evolution of simulated function-valued traits. Given function-valued data only from the tips of an evolutionary tree and utilising independent pri…
We extend in a minimal way the stylized model introduced in in "Tipping Points in Macroeconomic Agent Based Models" [JEDC 50, 29-61 (2015)], with the aim of investigating the role and efficacy of monetary policy of a `Central Bank' that sets the interest rate such as to steer the economy towards a prescribed inflation …
Machine learning identifies melting points in thermocouples for automatic calibration.
Financial markets, being spectacular examples of complex systems, display rich correlation structures among price returns of different assets. The correlation structures change drastically, akin to phase transitions in physical phenomena, as do the influential stocks (leaders) and sectors (communities), during market e…
Let V be a compact real analytic surface with isolated singularities embedded in , and assume its smooth part is equipped with a Riemannian metric that is induced from some analytic Riemannian metric on . We prove: 1. Each point of V has a neighborhood which is quasi-isometric (naturally and 'almost isometric…
The Support Vector Machine (SVM) of Vapnik (1998) has become widely established as one of the leading approaches to pattern recognition and machine learning. It expresses predictions in terms of a linear combination of kernel functions centred on a subset of the training data, known as support vectors. Despite its wide…
The paper classifies noncollapsed translators in 4D space.
Continuous process closes cusps in complex algebraic surfaces.
We consider the unnormalized Yamabe flow on manifolds with conical singularities. Under certain geometric assumption on the initial cross-section we show well posedness of the short time solution in the -setting. Moreover, we give a picture of the deformation of the conical tips under the flow by providing an asym…
Local Neural Operators enable efficient system-level analysis of complex PDEs.
Meta-causal states group equivalent qualitative causal dynamics, useful for analyzing system changes.
Low-rank matrix completion (LRMC) problems arise in a wide variety of applications. Previous theory mainly provides conditions for completion under missing-at-random samplings. This paper studies deterministic conditions for completion. An incomplete matrix is finitely rank- completable if there are at …
Among the central tenets of globalization is free migration of labor. Although much has been written about its benefits, little is known about the limitations of globalization, including how immigration affects the anti-globalist sentiment. Analyzing polls data, we find that over the last three years in a group of EU c…
The dynamic emulation of non-linear deterministic computer codes where the output is a time series, possibly multivariate, is examined. Such computer models simulate the evolution of some real-world phenomenon over time, for example models of the climate or the functioning of the human brain. The models we are interest…
We report analytical results for the development of the viscous fingering instability in a cylindrical Hele-Shaw cell of radius a and thickness b. We derive a generalized version of Darcy's law in such cylindrical background, and find it recovers the usual Darcy's law for flow in flat, rectangular cells, with correctio…
A great deal of attention has been recently given to Machine Learning (ML) techniques in many different application fields. This paper provides a vision of what ML can do in Power Line Communications (PLC). We firstly and briefly describe classical formulations of ML, and distinguish deterministic from statistical lear…
Manifold hypotheses are typically used for tasks such as dimensionality reduction, interpolation, or improving classification performance. In the less common problem of manifold estimation, the task is to characterize the geometric structure of the manifold in the original ambient space from a sample. We focus on the r…