Paper shows non-integrality of dike building model and provides conditions for integrality.
problem Determining the integrality of a dike building model for flood protection.
method Analyzes experimental data and mathematical proofs to establish conditions for integrality.
result Established non-integrality of the polytope and conditions for linear programming relaxation to be integral.
Deep learning model predicts wind-wave relationship.
problem Characterize ocean wave climate for engineering applications.
method Two-stage deep learning model: CNN for spatial features, LSTM for temporal dependencies.
result Predicts spatio-temporal relationship between wind and significant wave height.
Builds geometric structures for algebraic groups over real closed fields.
problem Characterizing and decomposing algebraic groups over specific valued fields.
method Real algebraic geometry to construct and analyze affine buildings.
result Computed stabilizers and obtained group decompositions.
Deep learning adapts HVAC models to new buildings.
problem Adapting thermal dynamics models to new buildings with limited data.
method Deep supervised domain adaptation (DSDA) using LSTM-based Sequence to Sequence model.
result Deep supervised domain adaptation improves predictive performance over learning from scratch.
Study Poisson boundaries of building lattices and generalize rigidity results.
problem Understanding Poisson boundaries of building lattices and their rigidity properties.
method Proved Poisson boundaries and used them to generalize rigidity results.
result Generalized rigidity results for morphisms and cocycles from lattices in buildings to groups with negative curvature.
We show that if a homeomorphism between the ideal boundaries of two Fuchsian buildings preserves the combinatorial cross ratio almost everywhere, then it extends to an isomorphism between the Fuchsian buildings. It follows that Mostow rigidity holds for Fuchsian buildings: if a group acts properly and cocompactly on tw…
We describe some buildings related to complex Kac-Moody groups. First we describe the spherical building of SLn(C) (i.e. the projective geometry PG(Cn)) and its Veronese representation. Next we recall the construction of the affine building associated to a discrete valuation on the rational function field C(z). Then …
Flat subsets in Euclidean buildings are contained within apartments.
problem Understanding the structure of flat subsets in Euclidean buildings.
method Proving containment within apartments.
result Convex flat subsets are contained in apartments.
The paper studies surface quotients of Fuchsian buildings.
problem Understanding group actions and symmetries in Fuchsian buildings.
method Developed theory of surface quotients, proved existence of discrete subgroups.
result Existence of discrete subgroups whose quotient is a compact surface.
Describes geometry of positive configurations in limiting buildings.
problem Understanding positive representations and their limits in buildings.
method Uses positivity properties of Hitchin representations and Parreau's compactification.
result Explicitly describes the geometry of preferred apartments in limiting buildings.
Research proves limits on harmonic map orders into Euclidean buildings.
problem Limits on the possible orders of harmonic maps from surfaces to Euclidean buildings.
method Direct analysis of homogeneous maps and related spherical billiards problem.
result The order of harmonic maps is of the form km where k divides ∣W∣. This paper surveys smart buildings using machine learning and big data.
problem Improving comfort and efficiency in smart buildings through data analysis.
method Survey of machine learning and big data techniques for smart buildings.
result Machine learning and big data are crucial for smart building services.
In this note, we show that the asymptotic dimension of any building is finite and equal to the asymptotic dimension of an apartment in that building.
New DNN architecture for indoor localization in multi-story buildings.
problem Scalable indoor localization in complex multi-story buildings.
method Stacked autoencoder and feed-forward classifier for multi-label classification.
result Near state-of-the-art performance with lower complexity and energy consumption.
We prove isoperimetric inequalities for quotients of n-dimensional Affine buildings. We use these inequalities to prove topological overlapping for the 2-dimensional skeletons of these buildings.
Harmonic maps to Euclidean buildings have rectifiable singular strata.
problem Understanding the structure of singular points for harmonic maps.
method Defining singular strata and proving rectifiability using the rectifiable Reifenberg program.
result Rectifiability of singular strata for harmonic maps into F-connected complexes. Automates building structural design with reduced mass and carbon footprint.
problem Time-consuming and laborious manual design process for buildings.
method Formulated building structures as graphs, trained end-to-end pipeline with a differentiable simulator.
result Optimal structural designs comparable to GA, with reduced building mass and carbon footprint.
This research reviews reinforcement learning for optimizing building energy management.
problem Optimizing energy utilization in building management systems.
method Comprehensive review of reinforcement learning applications in building energy management.
result Challenges and future directions in reinforcement learning for building energy management.
Paper models buildings' thermal characteristics with a Bayesian approach.
problem Modeling buildings' heat dynamics with various factors.
method Bayesian state-space model incorporating prior knowledge.
result Bayesian approach provides similar parameters as MCMC but faster.
Non-positively curved spaces admitting a cocompact isometric action of an amenable group are investigated. A classification is established under the assumption that there is no global fixed point at infinity under the full isometry group. The visual boundary is then a spherical building. When the ambient space is geode…
This paper constructs and proves the uniqueness of pluriharmonic maps to Euclidean buildings.
problem Existence and uniqueness of pluriharmonic maps to Euclidean buildings.
method Constructs a ρ-equivariant pluriharmonic map with specific asymptotic behavior and proves its uniqueness.
result Uniqueness of pluriharmonic maps to Euclidean buildings.
Deep learning model predicts window openings for commercial buildings.
problem Window openings are often biased and require tuning for each occupant.
method Deep learning model trained on occupant data from multiple buildings.
result Model achieves high evaluation accuracy and F1 scores.
Machine learning detects building damage in satellite images.
problem Extracting damage information from satellite imagery is slow and labor-intensive.
method Used four convolutional neural network models to detect damaged buildings.
result Models performed well in detecting damaged buildings in the 2010 Haiti earthquake.
In this paper we introduce, for each closed orientable surface, an analogue of Tits buildings adjusted to investigation of the Torelli group of this surface. It is a simplicial complex with some additional structure. We call this complex with its additional structure the Torelli building of the surface in question. The…
We introduce a construction turning some Coxeter and Davis realizations of buildings into systolic complexes. Consequently groups acting geometrically on buildings of triangle types distinct from (2,4,4), (2,4,5), (2,5,5), and various rank 4 types are systolic.
Deep learning detects building defects from images.
problem Time-consuming, laborious, and expensive traditional building condition assessment.
method Convolutional Neural Networks (CNN) with class activation mapping (CAM) for object localisation.
result Robust model accurately detects and localises building defects.
Deep learning outperforms classical methods in categorizing BIM images.
problem Classifying building designs from BIM models.
method Used classical machine learning (HOG + SVM) and deep learning models (pre-trained and custom-designed networks).
result Deep learning models achieve significantly higher accuracy (above 89%) compared to classical methods (57%).
In this article, we discuss the quasiconformal structure of boundaries of right-angled hyperbolic buildings using combinatorial tools. In particular we exhibit some examples of buildings of dimension 3 and 4 whose boundaries satisfy the combinatorial Loewner property. This property is a weak version of the Loewner prop…
Tangent Works won GEFCom 2017 using automatic model building.
problem Forecasting time series with historical temperature shuffling.
method Automatic model building using Tangent Information Modeller (TIM) with historical temperature shuffling and decision on trend variable.
result Automated model building setup won the competition.
Proves unique maps from certain spaces to others.
problem Uniqueness of equivariant harmonic maps into specific spaces.
method Analyzes maps into irreducible symmetric spaces and Euclidean buildings.
result Proves uniqueness of maps for certain actions.
Covering space theory is used to construct new examples of buildings.
In this paper, we give a general group-theoretic construction of affine $\RR$-buildings, and more generally, of affine Λ-buildings, associated to semisimple Lie groups over nonarchimedean real closed fields. The construction of Kleiner-Leeb using the asymptotic cone of a Riemannian symmetric space appears as a specia…
Graph2Diff neural network predicts precise code changes for build errors.
problem Fixing build errors in software development.
method Represented code and errors as graphs, used Graph Neural Network to predict precise diffs.
result Graph2Diff achieves over double the accuracy of DeepDelta in predicting precise code changes.
Proves regularity of harmonic maps into Euclidean buildings and applies to superrigidity of algebraic groups.
problem Regularity of harmonic maps into Euclidean buildings.
method Analyzes singular sets and applies geometric settings.
result Proves singular sets of Hausdorff codimension 2 for harmonic maps.
Transfer learning improves HVAC fault detection with minimal labeled data.
problem Lack of labeled data for HVAC system faults.
method Bayesian classifier trained on large data, then transferred to new buildings with few normal operation samples.
result Few samples are sufficient to maintain classifier precision and recall.
We compute the compactly supported cohomology of the standard realization of any locally finite building.
The relationship between minimal algebraic Kac-Moody groups and twin buildings is well known as is the relationship between formal completions in one direction and affine buildings. Nevertheless, as the completion of a Kac-Moody group in one direction destroys the opposite BN-pair, there exists no longer a twin buildin…
In this paper we show how to realize all knot (and link) types as C^{2} smooth curves of constant curvature. Our proof is constructive: we build the knots with copies of a fixed finite number of "building blocks" that are particular segments of helices and circles. We use these building blocks to construct all closed b…
The paper discusses building ETF risk models using a multilevel classification taxonomy.
problem Building accurate risk models for ETFs.
method First, build a multilevel classification taxonomy for ETFs. Then, use this taxonomy to define risk factors and build risk models.
result The approach can accurately classify and model ETF risks.
Novel probabilistic models forecast residential heating and electricity demand at hourly resolution.
problem Accurate hourly forecasting of residential heating and electricity demand.
method Probabilistic deep learning models trained on gas-heated region data.
result Significant improvement in forecast accuracy compared to NREL's ResStock model.
This survey is a brief introduction to the theory of hyperbolic buildings and their lattices, with a focus on recent results.
Deep learning boosts building energy load forecasting.
problem Short-term load forecasting in buildings.
method Stacked Boosters Network architecture with sparse interactions, parameter sharing, and equivariant representations.
result Outperforms state-of-the-art models in short-term load forecasting tasks.
We describe the set of possible vector valued side lengths of n-gons in thick Euclidean buildings of rank 2. This set is determined by a finite set of homogeneous linear inequalities, which we call the generalized triangle inequalities. These inequalities are given in terms of the combinatorics of the spherical Coxeter…
We show that twin building lattices have linear divergence, which implies that all asymptotic cones are without cut-points.
We study geodesically complete and locally compact Hadamard spaces X whose Tits boundary is a connected irreducible spherical building. We show that X is symmetric iff complete geodesics in X do not branch and a Euclidean building otherwise. Furthermore, every boundary equivalence (cone topology homeomorphism preservin…
New method builds volatility surfaces from quotes without arbitrage.
problem Building arbitrage-free implied volatility surfaces from market data.
method Sinkhorn's algorithm for optimal transport, proven convergence.
result Efficient numerical procedure for volatility surface construction.
A new SL strategy optimizes HVAC DR in multi-zone buildings.
problem Optimal DR of HVAC units in multi-zone buildings is challenging.
method Supervised learning with ANN replication and DNN integration.
result SLAMP achieves effective DR schedules with reduced computation time.
We generalize the natural cross ratio on the ideal boundary of a rank one symmetric spaces, or even CAT(−1) space, to higher rank symmetric spaces and (non-locally compact) Euclidean buildings - we obtain vector valued cross ratios defined on simplices of the building at infinity. We show several properties …