Results 61 to 70 of about 389,136 (225)

On the symmetrized S-divergence [PDF]

ITM Web of Conferences, 2019
In this paper we worked with the relative divergence of type s, s ∈ ℝ, which include Kullback-Leibler divergence and the Hellinger and χ2 distances as particular cases.
Simić Slavko
doaj   +1 more source

Maximally Divergent Intervals for Anomaly Detection

, 2016
We present new methods for batch anomaly detection in multivariate time series. Our methods are based on maximizing the Kullback-Leibler divergence between the data distribution within and outside an interval of the time series.
Barz, Björn, Bodesheim, Paul, Denzler, Joachim, Flach, Milan, Guanche, Yanira, Mahecha, Miguel, Reichstein, Markus, Rodner, Erik   +7 more
core   +1 more source

Efficient In‐Hardware Matrix–Vector Multiplication and Addition Exploiting Bilinearity of Schottky Barrier Transistors Processed on Industrial FDSOI

Advanced Electronic Materials, EarlyView.
ABSTRACT Machine learning and Artificial Intelligence (AI) tasks have stretched traditional hardware to its limits. In‐hardware computation is a novel approach that aims to run complex operations, such as matrix–vector multiplication, directly at the device level for increased efficiency.
Juan P. Martinez, Niladri Bhattacharjee, Yuxuan He, Giulio Galderisi, Brojogopal Sapui, Sara Mannaa, Ian O'Connor, Violetta Sessi, Peter Javorka, Thomas Mikolajick, Jens Trommer   +10 more
wiley   +1 more source

f-divergence Analysis of Generative Adversarial Network

Foundations of Computing and Decision Sciences
We aim to establish estimation bounds for various divergences, including total variation, Kullback-Leibler (KL) divergence, Hellinger divergence, and Pearson χ2 divergence, within the GAN estimator.
Hasan Mahmud, Sang Hailin
doaj   +1 more source

Entropy Concepts Applied to Option Pricing [PDF]

, 2016
Uncertainty is one of the most important concept in financial mathematics applications. In this paper we review some important aspects related to the application of entropy-related concepts to option pricing.
Tunaru, Radu
core  

Machine Learning Interatomic Potentials for Energy Materials: Architectures, Training Strategies, and Applications

Advanced Energy Materials, EarlyView.
Machine learning interatomic potentials bridge quantum accuracy and computational efficiency for materials discovery. Architectures from Gaussian process regression to equivariant graph neural networks, training strategies including active learning and foundation models, and applications in solid‐state electrolytes, batteries, electrocatalysts ...
In Kee Park, Saeed Pourasad, Jinhong Mun, Arunkumar Chitteth Rajan, Tae Hyeon Park, Anand Rohit, Mohammad Zafari, Tan‐Lien Pham, Eunjae Jung, Bonseung Koo, Miran Ha, Gi Beom Sim, Hyun Gyu Park, Won Woong Choi, Kwanghyeon Jo, Soohaeng Yoo Willow, David ChangMo Yang, Chang Woo Myung, Geunsik Lee, Kwang S. Kim   +19 more
wiley   +1 more source

Rényi Entropy and Rényi Divergence in Product MV-Algebras

Entropy, 2018
This article deals with new concepts in a product MV-algebra, namely, with the concepts of Rényi entropy and Rényi divergence. We define the Rényi entropy of order q of a partition in a product MV-algebra and its conditional version ...
Dagmar Markechová, Beloslav Riečan
doaj   +1 more source

Uniqueness and Optimality of Dynamical Extensions of Divergences

PRX Quantum, 2021
We introduce an axiomatic approach for channel divergences and channel relative entropies that is based on three information-theoretic axioms of monotonicity under superchannels, i.e., generalized data processing inequality, additivity under tensor ...
Gilad Gour
doaj   +1 more source

Bayesian Optimization Guiding the Experimental Mapping of the Pareto Front of Mechanical and Flame‐Retardant Properties in Polyamide Nanocomposites

Advanced Intelligent Discovery, EarlyView.
Bayesian optimization enabled the design of PA56 system with just 8 wt% additives, achieving limiting oxygen index 30.5%, tensile strength 80.9 MPa, and UL‐94 V‐0 rating. Without prior knowledge, the algorithm uncovered synergistic effects between aluminum diethyl‐phosphinate and nanoclay.
Burcu Ozdemir, Miguel Hernández‐del‐Valle, Christina Schenk, De‐Yi Wang, Maciej Haranczyk   +4 more
wiley   +1 more source

Kullback–Leibler divergence research for the simulation of the credit scoring [PDF]

, 2014
В роботі проведено теоретичне дослідження пошуку взаємозв’язку класичної відстані Кульбака-Лейблера та загальноприйнятих статистичних показників, що відображають щонайменше два напрямки практичного застосування у задачах бінарної класифікації, зокрема у
Soloshenko, Oleksandr, Солошенко, О. М.   +1 more
core