Framework for analyzing dynamic topological changes in point clouds using persistent homology and dynamic optimal transport.
problem Analyzing transient structural reorganizations during dynamic phase transitions in time-evolutionary point clouds.
method Hierarchical dynamic evaluation framework driven by topological and hypergraph reconstruction strategy.
result Combining transport-based alignment with multi-scale entropy diagnostics for dynamic topological analysis.
Optimal dividends for insurers with climate tipping point consideration.
problem Natural catastrophe claims and climate tipping point impact insurance profits.
method Two-dimensional stochastic control problems with Erlang distribution for tipping point timing, numerical approximation.
result Non-stationary climate tipping point can benefit shareholders by optimizing dividends.
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.
problem Detecting tipping points in complex, emergent systems.
method Combining manifold learning, neural networks, and Gaussian processes.
result Reduced-order models for mesoscopic and mean-field dynamics.
Minimal TIP and TIF found in compact spacetimes, impacting spacetime splitting.
problem Understanding the global structure of spacetimes with compact Cauchy surfaces.
method Analysis of Terminal Indecomposable Past (TIP) and Future (TIF) sets in spacetimes with compact Cauchy surfaces.
result In a spacetime with compact Cauchy surfaces, there is always at least one minimal TIP and one minimal TIF.
TIP-Search optimizes market prediction accuracy and timeliness under uncertain load.
problem Real-time market prediction requires accurate predictions before a deadline.
method Filters feasible models, dispatches workers, trades accuracy for deadline risk.
result Optimized pool achieves 0.991 timely accuracy and 0.994 raw accuracy.
TDA detects financial bubbles through early warning signals.
problem Detecting financial bubbles early.
method Using Log-Periodic Power Law Singularity (LPPLS) model to fit financial time series data.
result TDA generates early warning signals when LPPLS model fits the data.
CNMs detect tipping points in complex systems using causal network markers.
problem Identifying tipping points ahead of critical transitions in complex systems.
method Introducing CNMs that incorporate causality indicators to detect tipping points.
result CNMs show higher predictive power and accuracy than traditional DNB indicators.
TIP model improves POSE prediction with less resources.
problem Predicting polypharmacy side effects from drug-protein interactions.
method TIP model operates on three subgraphs for progressive representation learning.
result Improves accuracy by 7%+, time efficiency by 83imes, and space efficiency by 3imes. A new method identifies critical transitions in high-dimensional data.
problem Challenges in identifying critical transitions in high-dimensional time-series data.
method Spatial-temporal Principal Component Analysis (stPCA)
result Identifies tipping points before critical transitions reliably.
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 …
Model shows wealth taxes can cause sudden emigration waves, impacting GDP.
problem Estimating the economic impact of wealth taxes on emigration.
method Developed a social contagion model with tipping-point dynamics, embedded in Fokker-Planck framework.
result Micro-to-macro extrapolation requires five conditions to hold, violating each.
Gradient estimate for linearized translator equation in R^4.
problem Analyzing singularity models of mean curvature flow in R^4.
method Proving a gradient estimate for the variation field W in the tip region.
result Sharp bound for the derivative of the variation field W in the tip region.
Numerical simulations show stability of Type-II singularities in noncompact hypersurfaces.
problem Stability of Type-II singularities in noncompact hypersurfaces with rotationally-symmetric perturbations.
method Adaptation of the overlap method to include angular dependence.
result MCF of noncompact hypersurfaces with angular dependence behaves similarly to rotationally-symmetric perturbations, developing Type-II or Type-I singularities.
Let (M,g) be a surface with Riemannian metric and curved conic singularities. More precisely, a neighbourhood of a singularity is isometric to (0,1)×S1 with metric gconic=dr2+f(r)2dθ2,r∈(0,1). We study the spectral geometry of (M,g) using the heat trace expansion. We express the first few…
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…
Geometrically interpolates rigid body motions with initial and terminal twists.
problem Finding spatial trajectories between prescribed initial and terminal poses.
method Derives solutions for k-IV-TIP and k-BV-TIP for k=1,...,4.
result Automatic cubic interpolation identical to minimum acceleration curve when twists are zero.
Machine learning detects tipping points in complex systems.
problem Detecting abrupt shifts in complex dynamical systems.
method Equilibrium-informed neural networks (EINNs) trained on candidate equilibrium states.
result EINNs can identify critical thresholds in nonlinear systems.
Study of curvature blow-up in noncompact hypersurfaces using mean curvature flow.
problem Curvature blow-up in mean curvature flow of noncompact hypersurfaces.
method Rotationally symmetric solutions constructed with precise asymptotics.
result Highest curvature concentrates at the tip and blows up at rate (T−t)−1. The topology of SU(3)-representation varieties of the fundamental groups of planar webs so that the meridians are sent to matrices with trace equal to −1 are explored, and compared to data coming from spider evaluation of the webs. Corresponding to an evaluation of a web as a spider is a rooted tree. We associate t…
Study precise asymptotics of noncompact Type-IIb solutions to mean curvature flow.
problem Understanding the behavior of noncompact Type-IIb solutions to mean curvature flow as time approaches infinity.
method Constructed rotationally symmetric solutions with specific asymptotic behavior and analyzed their properties.
result The highest curvature concentrates at the tip of the hypersurface and blows up at the Type-IIb rate (2t+1)(γ−1)/2. Novel approach detects early warning indicators in complex systems.
problem Detecting abrupt transitions in complex systems.
method Directed anisotropic diffusion map and latent stochastic dynamical systems.
result Early warning indicators can detect tipping points in state transitions.
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.
problem Protecting personal data from unauthorized face recognition.
method Targeted identity-protection iterative method (TIP-IM) to generate adversarial identity masks.
result TIP-IM provides 95%+ protection success rate against face recognition models.
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…
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…
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…
The paper classifies noncollapsed translators in 4D space.
problem Classifying entire convex translators in 4D space.
method Developed Fredholm theory and used Lyapunov-Schmidt reduction.
result The one-parameter family of translators is uniquely determined.
Modeling how network connectivity affects economic collapse and robustness.
problem Impact of network topology on systemic risk and collapse of complex economic systems.
method Proposed a model to study the effects of network structure on economic systems by varying connectivity.
result Emergent systemic risks arise with increased interconnections, leading to phase transitions and tipping points.
The paper evaluates different graph input representations for urban network analysis.
problem Challenges in analyzing urban networks due to their size and complexity.
method Design and evaluation of six graph input representations considering topological and temporal characteristics.
result Temporal information in graph input representations significantly improves model accuracy (RMSE of 1.42).
Continuous process closes cusps in complex algebraic surfaces.
problem Developing cusps in Kähler-Einstein metrics on algebraic surfaces.
method Continuous cusp closing process via gluing construction.
result Cusps form in Kähler-Einstein metrics near isolated singularities.
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 Lq-setting. Moreover, we give a picture of the deformation of the conical tips under the flow by providing an asym…
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…
ACI identifies cause-effect relationships and causal influence ranges in dynamical systems.
problem Detecting and quantifying causal influence ranges in complex systems.
method Bayesian data assimilation and assimilative causal inference (ACI) to trace causes back from observed effects.
result Mathematically rigorous formulations of forward and backward causal influence ranges (CIRs) for nonlinear 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…
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…
This work analyzes SGGMs, offering convergence insights and practical design tips.
problem Theoretical convergence analysis for SGGMs with a system of coupled SDEs.
method Non-asymptotic convergence analysis for three graph generation paradigms.
result Unique factors affecting convergence in SGGMs and practical hyperparameter selection.
Study on heat equation and eigenfunctions on RCD spaces, proving unique continuation.
problem Unique continuation for caloric functions and eigenfunctions on RCD spaces.
method Establish weak unique continuation theorem for caloric functions and eigenfunctions on compact RCD(K,2) spaces.
result Existence of non-trivial eigenfunctions and caloric solutions vanishing up to infinite order at one point.
Study quantifies firm risks from nature decline, showing significant equity losses.
problem Estimating the financial impact of nature deterioration on companies.
method Developed metrics (Country Degradation Index, Nature Risk Score) and assessed five environmental hazards.
result Global equities lose 26.8% in a nature decline scenario, with worst firms losing 75%.
Open AI models affect bond yields differently than closed ones.
problem Understanding how market reactions to AI releases impact bond yields.
method Analyzed US bond yields before and after the release of open and closed AI models.
result Open AI models shift bond yields in the opposite direction of closed models.
Paper proves unique tangent flow at infinity for entropy-limited curve shortening.
problem Proving uniqueness of tangent flows for finite-entropy curve shortening.
method Rescaled backward convergence to a line, entropy analysis, and geometric properties.
result Ancient smooth curve shortening flow has a unique tangent flow at infinity.
The paper studies curvature properties under a specific type of flow on spaces with conical singularities.
problem Preserving curvature properties (Ricci curvature and scalar curvature) under a flow with conical singularities.
method Ricci de Turck flow, preserving conical structure, additional assumptions for scalar curvature positivity.
result Positivity of scalar curvature is preserved under the flow with additional assumptions.
We suggest an original physical approach to describe the mechanism of market pricing. The core of our approach is to consider pricing at different time scales separately, using independent equations of motion. Such an approach leads to a pricing model that not only allows estimating the volatility of future market pric…
Study Ricci flows on manifolds, proving they behave like self-similar solutions and confirming a conjecture.
problem Understanding the behavior of Ricci flows on higher-dimensional manifolds.
method Analyzing n-dimensional Ricci flows with non-negative Ricci curvature, starting at metric cones. result Ricci flows behave like self-similar solutions up to an exponential error in time.
Teaches deep learning to statisticians.
problem Statisticians lack expertise in deep learning.
method Developed a program and taught DL to statistics graduate students.
result Provided tips and resources for teaching DL.
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 …
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…