arXiv research

Introduces Causal Energy Minimization to understand Transformer layers.

New model predicts energy prices under different scenarios.

Eight different refinements of trapped surfaces are proposed, of three basic types, each intended as potential stability conditions. Minimal trapped surfaces are strictly minimal with respect to the dual expansion vector. Outer trapped surfaces have positivity of a certain curvature, related to surface gravity. Increas…

Paper adapts causal analysis for time-dependent systems, especially energy management.

Example of spacetime with causal bubbling, splitting into timelike and spacelike parts.

Geometric derivation of Einstein equations from causal fermion systems.

Paper uses Gaussian processes to handle shared latent confounders in causal inference.

ICIL learns policies invariant to multiple environments, improving generalization.

In Lorentzian manifolds of any dimension the concept of causal tensors is introduced. Causal tensors have positivity properties analogous to the so-called ``dominant energy condition''. Further, it is shown how to build, from ANY given tensor $A$, a new tensor quadratic in $A$ and ``positive'', in the sense that it is …

This paper presents a novel data-driven technique based on the spatiotemporal pattern network (STPN) for energy/power prediction for complex dynamical systems. Built on symbolic dynamic filtering, the STPN framework is used to capture not only the individual system characteristics but also the pair-wise causal dependen…

We show that the causal-future-directed character of the energy-momentum vector of $n$-dimensional asymptotically hyperbolic Riemannian manifolds with spherical conformal infinity, $n\ge 3$, can be traced back to that of asymptotically Euclidean general-relativistic initial data sets satisfying the dominant energy cond…

The study examines causal razors and their logical relations, highlighting a dilemma in causal discovery.

Energy game-theoretic frameworks have emerged to be a successful strategy to encourage energy efficient behavior in large scale by leveraging human-in-the-loop strategy. A number of such frameworks have been introduced over the years which formulate the energy saving process as a competitive game with appropriate incen…

Paper proves unique energy-minimizing curves in constrained spaces.

DCMA uses generative models to analyze treatment effects on entire outcome distributions.

DCMA uses generative models to analyze complex treatment effects on outcome distributions.

Paper proves various types of varieties minimize a specific energy.

The paper studies harmonic graphs in the Heisenberg group and their properties.

We show that K-energy minimizing movements agree with smooth solutions to Calabi flow as long as the latter exist. As corollaries we conclude that in a general Kahler class long time solutions of Calabi flow minimize both K-energy and Calabi energy. Lastly, by applying convergence results from the theory of minimizing …

Study energy-minimizing maps in projective spaces, proving sharp bounds.

The paper classifies energy-minimizing sets in specific domains.

Study finds surfaces in spherical caps that maximize modified energy.

We define a new class of knot energies (known as renormalization energies) and prove that a broad class of these energies are uniquely minimized by the round circle. Most of O'Hara's knot energies belong to this class. This proves two conjectures of O'Hara and of Freedman, He, and Wang. We also find energies not minimi…

This paper identifies the minimal set of nodes for optimal conditional interventions in causal bandits.

New method combines experimental and observational data for causal inference.

Smooth minimizers found for Willmore energy surfaces.

Optimal Euclidean structure minimizes energy in weighted toroidal graphs.

Researchers find optimal configurations of complex knots and links.

The paper proves a Fenchel theorem for Gauss maps and shows circles and disks minimize certain energies.

Framework calculates positional influence in causal residual Transformers.

In relativity, the energy of a moving particle depends on the observer, and the rest mass is the minimal energy seen among all observers. The Wang-Yau quasi-local mass for a surface in spacetime introduced in [7] and [8] is defined by minimizing quasi-local energy associated with admissible isometric embeddings of the …

We consider the task of causal structure learning over measurement dependence inducing latent (MeDIL) causal models. We show that this task can be framed in terms of the graph theoretic problem of finding edge clique covers,resulting in an algorithm for returning minimal MeDIL causal models (minMCMs). This algorithm is…

Study bounds the index of minimal submanifolds using energy measures and Yang-Mills-Higgs equations.

We investigate a discrete version of the Möbius energy, that is of geometric interest in its own right and is defined on equilateral polygons with $n$ segments. We show that the $Γ$-limit regarding $L^{q}$ or $W^{1,q}$ convergence, $q\in [1,\infty]$ of these energies as $n\to\infty$ is the smooth Möbius energy. This re…

The paper finds curves minimizing elastic energy pinned at endpoints.

New algorithm reduces regret in combinatorial causal bandits without graph structure.

The paper proves $\Gamma$-convergence of discrete tangent-point energies to continuous energies and ropelength, with applications to biarc curves.

Minimal submanifolds are found as energy concentration sets in variational problems.

Extended LPCMCI learns causal models from interventional data to minimize prediction error.

We study the converse to the statement that instantons are minimizers of the Yang--Mills energy in four dimensions. We show that given an energy minimizing connection, A, the curvature of A takes values in a subbundle of the adjoint bundle which decomposes as a sum of instantons.

Investigates energy minimizers and critical points of scale-invariant tangent-point energies for knots.

Minimal TIP and TIF found in compact spacetimes, impacting spacetime splitting.

New formula shows how causal vectors relate to mass-minimizing data.

New analysis identifies key factors in wildfire-generated thunderstorms.

One important effect of price shocks in the United States has been increased political attention paid to the structure and performance of oil and natural gas markets, along with some governmental support for energy conservation. This paper describes how price changes helped lead the emergence of a political agenda acco…

MO-CBO optimizes multiple outcomes in causal systems with minimal data.

Study on surfaces minimizing elastic energy with boundary constraints.

EMIX minimizes surprise in multi-agent reinforcement learning.