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.
Method captures fabric mechanics from depth images without expensive setups.
We introduce elastic geodesic grids for easy-to-fabricate, deployable structures.
New approach uses isotropic geometry to solve Euclidean problems.
In manufacture, steel and other metals are mainly cut and shaped during the fabrication process by computer numerical control (CNC) machines. To keep high productivity and efficiency of the fabrication process, engineers need to monitor the real-time process of CNC machines, and the lifetime management of machine tools…
Keywords: corporate finance, Wrocław University of Economics, net profit margin lub net sales profitability
We construct a number of sculptures, each based on a geometric design native to the three-dimensional sphere. Using stereographic projection we transfer the design from the three-sphere to ordinary Euclidean space. All of the sculptures are then fabricated by the 3D printing service Shapeways.
Scanning Transmission Electron Microscopy (STEM) has become the main stay for materials characterization on atomic level, with applications ranging from visualization of localized and extended defects to mapping order parameter fields. In the last several years, attention was attracted by potential of STEM to explore b…
Risk is part of the fabric of every business; surprisingly, there is little work on establishing best practices for systematic, repeatable risk identification, arguably the first step of any risk management process. In this paper, we present a proposal that constitutes a more holistic risk management approach, a method…
The paper develops methods for monitoring TPL machine health.
Confidential Guardian prevents model abstention from being used to discriminate.
New origami structures adapt to over 100 shapes with minimal actuation.
Computes elastic grids that approximate 3D surfaces without physical simulations.
In this paper, a spintronic neuromorphic reconfigurable Array (SNRA) is developed to fuse together power-efficient probabilistic and in-field programmable deterministic computing during both training and evaluation phases of restricted Boltzmann machines (RBMs). First, probabilistic spin logic devices are used to devel…
NAS improves gliomas segmentation on MRI scans.
This paper shows how we can build a model for transactions when goods are given away in the expectation of a later settlement. In settings where people keep track of their social accounts we are able to redefine concepts like account balance, yield curve and the law of diminishing returns. The model provides us with a …
In this note, we derive a new logarithmic Sobolev inequality for the heat kernel on the Heisenberg group. The proof is inspired from the historical method of Leonard Gross with the Central Limit Theorem for a random walk. Here the non commutative nature of the increments produces a new gradient which naturally involves…
Scientific and engineering processes deliver massive high-dimensional data sets that are generated as non-linear transformations of an initial state and few process parameters. Mapping such data to a low-dimensional manifold facilitates better understanding of the underlying processes, and enables their optimization. I…
Spatial separation of suspended particles based on contrast in their physical or chemical properties forms the basis of various biological assays performed on lab-on-achip devices. To electronically acquire this information, we have recently introduced a microfluidic sensing platform, called Microfluidic CODES, which c…
Gaussian processes model sparse data in astrophysics and chemistry.
Blockchain technology shows significant results and huge potential for serving as an interweaving fabric that goes through every industry and market, allowing decentralized and secure value exchange, thus connecting our civilization like never before. The standard approach for asset value predictions is based on market…
As the advancement of information security, human recognition as its core technology, has absorbed an increasing amount of attention in the past few years. A myriad of biometric features including fingerprint, face, iris, have been applied to security systems, which are occasionally considered vulnerable to forgery and…
Recently, increased computational power and data availability, as well as algorithmic advances, have led machine learning techniques to impressive results in regression, classification, data-generation and reinforcement learning tasks. Despite these successes, the proximity to the physical limits of chip fabrication al…
Paper proposes conditional multidimensional scaling for better data reduction.
Transformations of macroeconomic data affect machine learning forecasts, especially with regularization and nonlinearity.
During the fabrication of casting parts sensor data is typically automatically recorded and accumulated for process monitoring and defect diagnosis. As casting is a thermal process with many interacting process parameters, root cause analysis tends to be tedious and ineffective. We show how a decomposition based on non…
A machine-learning method speeds up RIS design by predicting reflection coefficients.
Understanding cities is central to addressing major global challenges from climate and health to economic resilience. Although increasingly perceived as fundamental socio-economic units, the detailed fabric of urban economic activities is only now accessible to comprehensive analyses with the availability of large data…
Bayesian optimisation is a sample-efficient search methodology that holds great promise for accelerating drug and materials discovery programs. A frequently-overlooked modelling consideration in Bayesian optimisation strategies however, is the representation of heteroscedastic aleatoric uncertainty. In many practical a…
New system resists meme coin copy trading bots.
Develops a new theory for approximating functions on massive data.
Designs chiral photonic structures using machine learning for efficient optical properties.
Wrist movements can reveal digits, posing security risks.
Python scripts analyze MRAM-based neuromorphic devices' process variation impacts on machine learning accuracy.
GeoHNN models physics laws for stable, accurate predictions.
Numerical optimization is an important tool in the field of computational physics in general and in nano-optics in specific. It has attracted attention with the increase in complexity of structures that can be realized with nowadays nano-fabrication technologies for which a rational design is no longer feasible. Also, …
Paper presents attacks on real-time object detection systems.
New method reduces uncertainty in high-dimensional circuits by automatically determining tensor rank and adaptive sampling.
New method enhances hotspot prediction in IC designs.
New method uses graphene transistors for efficient non-uniform random number generation.
ANN model predicts zinc leaching filter cake moisture accurately.
Task-agnostic data valuation without validation requirements.
Method estimates travel times on urban roads using Uber data.
Work addresses long-term accuracy issues in IoT air quality sensors.
Paper presents ADEPOS framework for energy-efficient anomaly detection.
Azure (the cloud service provided by Microsoft) is composed of physical computing units which are called nodes. These nodes are controlled by a software component called Fabric Controller (FC), which can consider the nodes to be in one of many different states such as Ready, Unhealthy, Booting, etc. Some of these state…
In this paper we study dynamic pricing mechanisms of financial derivatives. A typical model of such pricing mechanism is the so-called g--expectation defined by solutions of a backward stochastic differential equation with g as its generating function. Black-Scholes pricing model is a special linear case of this pricin…
A solution for the Weinstein's Problem in the general framework of generalized Lie algebroids is the target of this paper. We present the mechanical systems called by use, mechanical (?; ?)-systems, Lagrange mechanical (?; ?)-systems or Finsler mechanical (?; ?)-systems and we develop their geometries. We obtain the ca…
New mechanics on non-associative octonions discovered.