arXiv research

Modeling energy facility dynamics using cointegrating jumps.

Hybrid AI methods optimize renewable energy and facilities management.

Study on energy storage's impact on electricity prices and profitability.

The paper addresses fairness in facility location by considering local population densities.

This paper develops a framework for predicting patient workload across multiple VA facilities.

Paper provides a method to price electricity storage contracts using COS technique.

Optimizes energy storage under fluctuating prices and partial information.

Paper tackles online facility location with user requests and provides a quasi-linear time algorithm.

The method optimizes facility deployment schedules to meet fuel cycle demands efficiently.

Boosting models improve pediatric ICU transfer prediction.

Data-driven assistants predict congestion to optimize shared facilities efficiency.

Proposes a new method to find overconfident predictions in classifiers.

MPNN improves on UniFL approximation with provable guarantees.

Deployable probabilistic programming for Go and other languages.

Decentralized algorithm reduces regret and converges to Nash equilibrium in online congestion games.

Study examines how industrial emissions evolve over time in response to various factors.

SimTensor generates synthetic tensor data for research.

Deep learning for particle classification on large event images.

Trading floors need to be twice as deep as electronic markets to compete.

New tools analyze data selection methods, reducing information losses.

Develops a Bayesian model to predict business revenue and demand.

Bayesian inference calibrates Hall thruster model uncertainty at varying pressures.

Trans-GLMC tackles source heterogeneity in transfer learning for structured clusters.

Paper shows how to efficiently summarize large datasets using sparsity.

The paper optimizes daily storage trading of electricity using dynamic spread densities.

Apricot selects subsets from large data sets efficiently using submodular optimization.

Proposes a graph neural network for traffic forecasting in WANs.

The paper tackles Nash-regret minimization in congestion games with bandit feedback.

A new batch Bayesian optimization method reduces computation time.

Two diversity models improve subset selection for image classification tasks.

This paper focuses on the valuation and hedging of gas storage facilities, using a spot-based valuation framework coupled with a financial hedging strategy implemented with futures contracts. The first novelty consist in proposing a model that unifies the dynamics of the futures curve and the spot price, which accounts…

Stochastic programs simplify complex models with noise and nondeterminism.

R package for machine learning in survival analysis.

Deep learning optimizes gas storage operations.

This paper describes the algorithms, features and implementation of PyDEC, a Python library for computations related to the discretization of exterior calculus. PyDEC facilitates inquiry into both physical problems on manifolds as well as purely topological problems on abstract complexes. We describe efficient algorith…

Enumerating all 3-manifold triangulations of a given size is a difficult but increasingly important problem in computational topology. A key difficulty for enumeration algorithms is that most combinatorial triangulations must be discarded because they do not represent topological 3-manifolds. In this paper we show how …

This paper introduces an agent-based artificial financial market in which heterogeneous agents trade one single asset through a realistic trading mechanism for price formation. Agents are initially endowed with a finite amount of cash and a given finite portfolio of assets. There is no money-creation process; the total…

AI predicts medical specialty diagnostic choices from EHR records.

Developing a visual platform for faster astronomical source cataloging.

The study improves load forecasting for electricity consumers using advanced machine learning models.

Machine learning detects underwater gas leaks.

Universal neural network encoder learns from diverse time series data.

Fink AGN classifier achieves high accuracy in classifying active galactic nuclei.

LSTM model detects voice disorders with high accuracy.

SlicStan improves Stan's usability and efficiency.

Extended Möbius energy formula for generalized O'Hara's energies.

This paper studies four trading algorithms of a professional trader at a multilateral trading facility, observing a realistic two-sided limit order book whose dynamics are driven by the order book events. The identity of the trader can be either internalizing or regular, either a hedge fund or a brokery agency. The spe…

Holographic energy equals Hamiltonian energy.