A locally-built, LLM-digested index of recent arXiv papers in quant finance, geometry/topology, and statistical ML — keyword search served straight from SQLite on this machine.
The study investigates noise effects on parameter estimation for Ornstein-Uhlenbeck processes.
Paper uses VAEs to detect radar targets in complex noise.
SVDD and Deep SVDD improve radar target detection in clutter.
This work generates synthetic 3D thermal facial data using 2D facial data and deep learning.
In the emerging advancement in the branch of autonomous robotics, the ability of a robot to efficiently localize and construct maps of its surrounding is crucial. This paper deals with utilizing thermal-infrared cameras, as opposed to conventional cameras as the primary sensor to capture images of the robot's surroundi…
ARX models predict thermal behavior of WBG semiconductors accurately.
The study applies wealth thermalization hypothesis to social networks and explains inequality.
Study on uniquely determining thermal properties from boundary temperature and heat flux measurements.
With the fast growth in the visual surveillance and security sectors, thermal infrared images have become increasingly necessary ina large variety of industrial applications. This is true even though IR sensors are still more expensive than their RGB counterpart having the same resolution. In this paper, we propose a d…
Power and thermal management are critical components of High-Performance-Computing (HPC) systems, due to their high power density and large total power consumption. The assessment of thermal dissipation by means of compact models directly from the thermal response of the final device enables more robust and precise the…
Generative thermal design learns optimal shapes using multi-agent reinforcement learning.
On curved spaces, viscous fluids reach equilibrium quickly.
A modified GAN improves thermal comfort classification models by balancing imbalanced datasets.
Study finds almost contact structures in thermal QCD-like theories at intermediate coupling.
We propose a novel receiver for orthogonal frequency division multiplexing (OFDM) transmissions in impulsive noise environments. Impulsive noise arises in many modern wireless and wireline communication systems, such as Wi-Fi and powerline communications, due to uncoordinated interference that is much stronger than the…
BODE enhances deep neural network predictions and uncertainty quantification in safety modeling.
Paper addresses LSTM stability for thermal systems using infinity-norm.
CNN accurately reconstructs lattice topology with strong thermal fluctuations.
The world GDP distribution is described using thermodynamics principles.
The thermal subsystem of the Mars Express (MEX) spacecraft keeps the on-board equipment within its pre-defined operating temperatures range. To plan and optimize the scientific operations of MEX, its operators need to estimate in advance, as accurately as possible, the power consumption of the thermal subsystem. The re…
Study of -theory dual of thermal QCD-like theories at intermediate coupling.
We introduce a novel non-parametric methodology to test for the dynamical time evolution of the lag-lead structure between two arbitrary time series. The method consists in constructing a distance matrix based on the matching of all sample data pairs between the two time series. Then, the lag-lead structure is searched…
Personal income distribution in the USA has a well-defined two-class structure. The majority of population (97-99%) belongs to the lower class characterized by the exponential Boltzmann-Gibbs ("thermal") distribution, whereas the upper class (1-3% of population) has a Pareto power-law ("superthermal") distribution. By …
Thermal dynamics modeling has been a critical issue in building heating, ventilation, and air-conditioning (HVAC) systems, which can significantly affect the control and maintenance strategies. Due to the uniqueness of each specific building, traditional thermal dynamics modeling approaches heavily depending on physics…
Study chaotic dynamics in social stratification models leading to thermalization and turbulence.
Thermalizer stabilizes autoregressive models for long-term predictions in chaotic systems.
Study examines how twisting graphene nanoribbons affects their thermal conductivity.
The large thermal capacity of buildings enables heating, ventilating, and air-conditioning (HVAC) systems to be exploited as demand response (DR) resources. Optimal DR of HVAC units is challenging, particularly for multi-zone buildings, because this requires detailed physics-based models of zonal temperature variations…
Improved person detection in occluded conditions with AOS images.
Thermal preferences vary from person to person and may change over time. The main objective of this paper is to sequentially pose intelligent queries to occupants in order to optimally learn the indoor air temperature values which maximize their satisfaction. Our central hypothesis is that an occupant's preference rela…
Method infers causal structure from system behaviors using RKHS and kernel -machines.
We have recently introduced the ``thermal optimal path'' (TOP) method to investigate the real-time lead-lag structure between two time series. The TOP method consists in searching for a robust noise-averaged optimal path of the distance matrix along which the two time series have the greatest similarity. Here, we gener…
A popular approach for predicting the future of dynamical systems involves mapping them into a lower-dimensional "latent space" where prediction is easier. We show that the information-theoretically optimal approach uses different mappings for present and future, in contrast to state-of-the-art machine-learning approac…
New method predicts heat load in thermal grids using latent variables.
New formalism solves kinematical constraints in curved backgrounds and non-trivial states.
Study examines how economic policy uncertainty impacts stock markets.
Generalizes embedding formalism for CFTs on curved backgrounds.
Meta-learning algorithms prepare quantum Gibbs states efficiently for NISQ devices.
Recent results and interpretations are presented for the thermal minority game, concentrating on deriving and justifying the fundamental stochastic differential equation for the microdynamics.
Learning influence pathways of a network of dynamically related processes from observations is of considerable importance in many disciplines. In this article, influence networks of agents which interact dynamically via linear dependencies are considered. An algorithm for the reconstruction of the topology of interacti…
Quantum annealers aim at solving non-convex optimization problems by exploiting cooperative tunneling effects to escape local minima. The underlying idea consists in designing a classical energy function whose ground states are the sought optimal solutions of the original optimization problem and add a controllable qua…
We consider the problem of optimal trading for a power producer in the context of intraday electricity markets. The aim is to minimize the imbalance cost induced by the random residual demand in electricity, i.e. the consumption from the clients minus the production from renewable energy. For a simple linear price impa…
Dual ML approach predicts peak temperatures in AFSD, improving process optimization.
Modeling buildings' heat dynamics is a complex process which depends on various factors including weather, building thermal capacity, insulation preservation, and residents' behavior. Gray-box models offer a causal inference of those dynamics expressed in few parameters specific to built environments. These parameters …
We study a minimalist kinetic model for economies. A system of agents with local trading rules display emergent demand behaviour. We examine the resulting wealth distribution to look for non-thermal behaviour. We compare and contrast this model with other similar models.
A 'holographic formula' expressing the functional determinant of the scattering operator in an asymptotically locally anti-de Sitter(ALAdS) space has been proposed in terms of a relative functional determinant of the scalar Laplacian in the bulk. It stems from considerations in AdS/CFT correspondence of a quantum corre…
The paper proposes a Gibbs sampler for neural network posterior sampling.
A thermodynamic theory explains EU election vote distributions.