Verify provably fair dice yourself: check the server seed hash, compute HMAC-SHA256, convert the digest to a roll, with a ...

Stochastic gradient descent and Adam are optimization algorithms that update model parameters from estimated gradients, but they use different rules for momentum and per-parameter step sizes. This ...

INTRODUCTION Arctic near-surface temperatures are rising at nearly four times the global mean rate (1, 2). This amplification peaks in winter (3, 4), when the absence of sunlight leaves the surface ...

Equipping students with a range of transferable skills in mathematical modelling, analysis and computation for employment in industry and future research. This course provides training in many ...

This repository contains an implementation of the Sig-SDEs model as described in the research paper: Sig-SDEs model for quantitative finance by Imanol Perez Arribas, Cristopher Salvi, and Lukasz ...

Abstract: We study the problem of constructing controlled supermartingale functions to synthesize feedback laws that guarantee safety properties of stochastic differential equations (SDE) with control ...

Distributions: Normal, Gamma, Non-Central Chi-Squared (some functions are delegated to Apache commons-math). Models: Black Scholes, Bachelier, SABR, ZABR, CEV, etc. The library is available for Java ...

Dynamic tumor-microenvironment interactions greatly affect growth and drug resistance, highlighting the importance and challenge of developing mathematical models to optimize treatment schedules. Here ...

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. In this paper, we show how kernel-based models for the Koopman generator─the gEDMD ...

Silent data errors are raising concerns in large data centers, where they can propagate through systems and wreak havoc on long-duration programs like AI training runs. SDEs, also called silent data ...