The paper analyzes frameworks for integrating sustainability into investment decisions.
problem Understanding how ESG factors influence investment choices.
method Examined and analyzed various theoretical frameworks including Behavioral Finance, Modern Portfolio, and Risk Management.
result Investors increasingly integrate ESG factors to optimize financial outcomes and societal goals.
Develops a framework for 1D geometric field theories and proves they are equivalent to vector bundles.
problem Classifying 1D geometric field theories.
method Formalizes geometric functorial field theories with geometric structures and smooth variations.
result 1D field theories are equivalent to vector bundles with connection and bilinear pairing.
Survey of three geometric frameworks for action-dependent field theories.
problem Understanding action-dependent field theories through geometric structures.
method Introduction and analysis of three geometric frameworks: k-contact, k-cocontact, and multicontact.
result Analysis of relationships among these geometric structures and comparison with other definitions.
New geometric framework for non-conservative field theories with time-dependent terms.
problem Describing non-conservative field theories with explicit space-time dependence.
method Combining k-cosymplectic and k-contact formulations to develop Hamiltonian and Lagrangian formalisms.
result Illustrated with the nonlinear damped wave equation, demonstrating the new formalism's applicability.
Develops a new geometric framework for non-conservative field theories.
problem Non-conservative field theories in classical physics.
method Multisymplectic and contact geometries, variational field equations, jet bundle description.
result Introduces variational field equations in multicontact manifolds.
Paper introduces Floer theory for field theories, proving periodic solutions for particle-field systems.
problem Defining Hamiltonian Floer theory for covariant field theories, especially those with degenerate action functionals.
method Regularization procedure to handle degeneracy, leading to Floer curves that converge to periodic solutions.
result Existence of Floer curves and space-time periodic solutions for coupled particle-field systems.
Unified approach to totally ramified values in various surface theories.
problem Totally ramified values in value distribution theory, normal family theory, and Gauss maps of surfaces.
method Bloch--Ros principle applied to various surface theories.
result Unified approach to phenomena concerning totally ramified values.
Develops a new framework for anomaly description in quantum field theories.
problem Anomalies in quantum field theories.
method Extended functorial field theories and symmetric monoidal bicategories.
result Explicit construction of anomaly 2-cocycles and 't Hooft anomalies.
New framework for conformal equivariant cycles in KK-theory.
problem Tackles conformal equivariance in unbounded KK-theory.
method Extends unbounded Kasparov theory with novel perturbation theory.
result Defines new unbounded representatives of Kasparov classes.
Novel multisymplectic framework for pseudo-Fueter curves in Hamiltonian field theory.
problem Generalizing Floer theory to multisymplectic geometry.
method Introducing pseudo-Fueter curves in a compatible almost hyperkähler structure.
result Gradient lines of multisymplectic action functional are pseudo-Fueter curves.
New framework connects two neural network theories, improving finite-width approximations.
problem Theoretical guarantees for neural network training in general cases.
method Developed a general framework linking mean-field and constant kernel theories.
result Discrete-time MF limit provides better approximation for finite-width nets.
Unified framework for Morita invariant cohomology of Lie groupoids.
problem Proving Morita invariance of cohomology theories for Lie groupoids.
method Viewing cohomology as sheaves of modules on the nerve of the groupoid and establishing criteria for Morita invariance.
result Established criteria for Morita invariant cohomology theories.
Develops a statistical framework for coherent risk estimation.
problem Constructing coherent risk estimators with sound financial and statistical properties.
method Inspired by axiomatic risk measure theory, defines coherent risk estimators through robust representations linked to L-estimators. result Demonstrates that coherence of a risk measure does not necessarily carry over to its estimators and shows alternative weight structures can lead to different outcomes.
Unified framework for feature-based explanations using ANOVA and game theory.
problem Differences between feature-based explanations methods limit their applicability.
method Introduces a unified framework combining fANOVA and cooperative game theory.
result Uncovered similarities and differences between various explanation techniques.
We develop a new geometric framework suitable for dealing with Hamiltonian field theories with dissipation. To this end we define the notions of k-contact structure and k-contact Hamiltonian system. This is a generalization of both the contact Hamiltonian systems in mechanics and the k-symplectic Hamiltonian syst…
Complex network theory has been applied to solving practical problems from different domains. In this paper, we present a general framework for complex network applications. The keys of a successful application are a thorough understanding of the real system and a correct mapping of complex network theory to practical …
New framework using Jensen-Shannon divergence improves domain adaptation theory.
problem Incoherence between empirical domain adversarial training and theoretical H-divergence. method Established new theoretical framework based on Jensen-Shannon divergence, derived bi-directional upper bounds.
result Framework exhibits flexibilities for various transfer learning problems.
In this short note we show how Dubrovin's integrable hierarchies, defined using the Gromov-Witten theory of a closed symplectic manifold, generalizes to Hamiltonian Floer theory. In particular, we show how the required generalization of the PSS isomorphism, relating Gromov-Witten theory and Hamiltonian Floer theory, ca…
Jets of mappings introduced by Ehresmann are still the most useful objects for formulating geometric frameworks of physical theories. We are proposing modifications designed to make jet theory less dependent on local coordinates. Extensions of the theory with applications to the calculus of variations and mechanics are…
Utility and risk are two often competing measurements on the investment success. We show that efficient trade-off between these two measurements for investment portfolios happens, in general, on a convex curve in the two dimensional space of utility and risk. This is a rather general pattern. The modern portfolio theor…
Abstracts discuss a common framework for constructing homology theories.
problem Developing homology theories in low-dimensional topology and geometry.
method Uses a common framework since the late 1980s to construct homology theories.
result Indicates the specific nature of the situation dictates the algebraic nature of chain groups.
Introduces a new geometric framework for non-perturbative BV-theory.
problem Non-perturbative generalization of BV-theory in infinite-dimensional spaces.
method Derived differential geometry and homotopical algebraic geometry.
result Concrete model of derived smooth stacks for encoding non-perturbative BV-theory.
Propose a model-independent axiomatic framework for derived skein theory.
problem Derived skein theory of oriented 3-manifolds with coefficients in a ribbon tensor category.
method Design axioms for the 0th homology and gluing.
result Establishes relationships between derived and ordinary skein theory.
This paper develops a geometric framework for Wilson surfaces in higher gauge theory.
problem Quantum field theory of Wilson surfaces in higher gauge theory.
method Higher coadjoint orbit theory and derived geometric framework.
result Identification of derived coadjoint orbits and their quantization.
Proposes IPT for modeling complex joint distributions.
problem Lack of closed-form solutions for complex continuous or mixed distributions.
method Observer-centered framework with three independence axioms; derivation of closed-form solutions.
result Closed-form solutions for complex joint distributions under IPT.
Simplified construction recovers Todd class using algebraic methods.
problem Recovering Todd class from a JLO-type cocycle.
method Algebraic framework, Dirac operator, new trace.
result Recovery of Todd class using novel methods.
We consider the "partial information decomposition" (PID) problem, which aims to decompose the information that a set of source random variables provide about a target random variable into separate redundant, synergistic, union, and unique components. In the first part of this paper, we propose a general framework for …
Novel CMG framework improves financial sentiment forecasting.
problem Challenges in short-term sentiment forecasting of financial OHLC data.
method Integrates chaos theory, Markov chains, and Gaussian processes with transformer models.
result Consistently outperforms traditional models in accuracy and efficiency.
Operationalizes engagement as human behavior, linking theory and data.
problem Fuzziness of engagement concept.
method Formal framework, Melchoir Model, model comparison, theory-driven hypothesis.
result Engagement can be shaped and interpreted using data-driven methods.
New framework ensures valid uncertainty estimates for any data stream changes.
problem Challenges of distribution shifts and adversarial actors in real-world data streams.
method Leveraging Blackwell approachability from game theory, the framework guarantees calibrated uncertainties for any compact space.
result Improves calibration and decision-making for energy systems.
SVR analyzed within RQ framework for risk management.
problem Risk management in stochastic optimization.
method Risk Quadrangle (RQ) theory applied to SVR.
result SVR formulations as minimization of Vapnik error and CVaR norm.
Extends Lie bialgebroids for string and M theories with new calculus framework.
problem Formalize calculus on algebroids for string and M theories.
method Reinterpret matched pairs of Leibniz algebroids, examine algebroid axioms, construct double on direct sum.
result Construct Drinfel'd double of Lie bialgebroids for general algebroids.
Theoretical framework for data augmentation in finance improves portfolio construction.
problem Improving portfolio construction in speculative markets.
method Developed a theoretical framework for data augmentation and regularization in deep learning for finance.
result A simple noise injection algorithm improves portfolio construction over no noise.
Paper explores rough path theory for frictionless markets, linking NCFL to unbiased rough integrators.
problem Tackles the limits of rough path theory in frictionless markets.
method Investigates the capacity of rough path theory to support No Free Lunch markets.
result Establishes a 'Rough Kreps-Yan' theorem linking NCFL to unbiased rough integrators.
A framework for analyzing regularizers to ensure trustworthy theory-driven model estimation.
problem Uncertain choice of regularizers can compromise the interpretability of deep grey-box models.
method Adapting neural net architecture and training objective to analyze regularizer behavior empirically.
result Empirical analysis of regularizers helps in making a justified choice for trustworthy theory-driven model estimation.
Mathematical framework to understand neural network vulnerability.
problem Understanding and quantifying adversarial vulnerability in neural networks.
method Develops a geometric framework using Ricci curvature to measure decision boundaries and adversarial perturbations.
result Establishes a new theory linking adversarial attacks to Ricci curvature of decision boundaries.
Unified framework for 3D and 4D manifold and knot theory.
problem Unified understanding of manifold and knot theory.
method Unified correspondence between different subfields of low-dimensional topology.
result Unified algebraic manifestations of 3D and 4D manifold and knot theory.
Develops invariants for webs and foams using Seiberg-Witten theory.
problem Computing invariants for complex geometric structures.
method Monopole Floer homology with orbifold singularities.
result New invariants for webs and foams.
New framework learns interaction rules from animal trajectories.
problem Challenges in extracting interaction rules from animal movement data.
method Augmented behavioral models with neural networks and theory-guided regularization.
result Improved performance over baselines and novel biological insights.
In this thesis, we study deformations of compact holomorphic Poisson manifolds and algebraic Poisson schemes in the framework of Kodaira-Spencer's analytic deformation theory and Grothendieck's algebraic deformation theory.
This paper presents relevant modern mathematical formulations for (classical) gauge field theories, namely, ordinary differential geometry, noncommutative geometry, and transitive Lie algebroids. They provide rigorous frameworks to describe Yang-Mills-Higgs theories or gravitation theories, and each of them improves th…
We provide a unified framework for proving Reidemeister-invariance and functoriality for a wide range of link homology theories. These include Lee homology, Heegaard Floer homology of branched double covers, singular instanton homology, and \Szabo's geometric link homology theory. We follow Baldwin, Hedden, and Lobb (a…
Paper develops a new kernel approximation framework.
problem High time and space complexity of kernel methods for large datasets.
method Perturbation-based kernel approximation framework using classical perturbation theory.
result Framework generalizes and improves upon existing methods.
Paper presents a Bayesian-decision-theory framework for long-tailed classification.
problem Heavy imbalance and asymmetric misprediction costs in long-tailed datasets.
method Bayesian-decision-theory perspective, unifying re-balancing and ensemble methods.
result Improves accuracy for all classes, especially tails, with provably optimal decisions.
At the heart of technology transitions lie complex processes of social and industrial dynamics. The quantitative study of sustainability transitions requires modelling work, which necessitates a theory of technology substitution. Many, if not most, contemporary modelling approaches for future technology pathways overlo…
We present a simple theoretical framework, and corresponding practical procedures, for comparing probabilistic models on real data in a traditional machine learning setting. This framework is based on the theory of proper scoring rules, but requires only basic algebra and probability theory to understand and verify. Th…
Geometrically classifies maps from R^0|2 to any manifold, unifying theories.
problem Classifying maps from R^0|2 to any manifold without auxiliary structures.
method Relates maps to pullback of decomposable bivector bundle over S via algebraic constraints.
result Reduced manifold has fiber dimension dim(S) + 1, unifying topological and algebraic views.
New model calculates Wilson surfaces in higher gauge theory.
problem Calculating Wilson surfaces in higher gauge theory.
method Derived geometric framework, topological coadjoint orbit model, functional integral framework.
result Strong evidence that model underlies Wilson surfaces partition function.