Results 51 to 60 of about 255,317 (213)

Kullback-Leibler Divergence.

, 2016
(A) Bar graph showing family (upper) and genus (lower) level Kullback-Leibler divergence (y-axis) for 6 regions (x-axis). Known mock compared to observed mock (EvHi, purple; EvLo green; StHi red; StLo blue) for forward reads.
Ann Cashion (395431), Andrew J. Oler (2171533), Jennifer J. Barb (17524), Natalia Chalmers (2171530), Hyung-Suk Kim (361518), Gwenyth R. Wallen (703544), Peter J. Munson (17525), Nancy J. Ames (123698)   +7 more
core   +1 more source

High‐Throughput Screening for Accelerated Oxide Glass Discovery

Advanced Science, EarlyView.
A high‐throughput screening platform is presented that allows for accelerating laboratory glass synthesis by a factor of 102, using multicomponent stereolithographic printing. Automatic sample evaluation is achieved via Raman spectroscopy and similarity analysis without any sample preparation.
Igor Seibel‐Geraschenko, Josef Slowik, Franziska Scheffler, Alexis Duval, N. M. Anoop Krishnan, Lothar Wondraczek   +5 more
wiley   +1 more source

Molecular Atlas of Key Food Odorants Reveals Mixture‐Level Organization and Enables Generative Aroma Design

Advanced Science, EarlyView.
KFO‐Atlas reveals how real‐world aromas are organized as structured mixtures rather than individual molecules. Building on these principles, KFO‐Gen, a generative AI framework, designs perceptually valid aroma formulations and reconstructs meat‐like aromas exclusively from plant‐derived odorants, providing a foundation for mixture‐level studies and AI ...
Jingzhi Zhang, Huadong Xing, Antonella Di Pizio, Qinfei Ke, Xingran Kou, Dachuan Zhang   +5 more
wiley   +1 more source

Technical Notes on Kullback-Leibler Divergence

, 2018
I provide some technical notes regarding the Kullback-Leibler divergence. Derivations of the Kullback-Leibler divergence are provided for Bernoulli, Geometric, Poisson, Exponential, and Normal ...
Alexander Etz
core   +1 more source

Bounds for Kullback-Leibler divergence

Electronic Journal of Differential Equations, 2016
Entropy, conditional entropy and mutual information for discrete-valued random variables play important roles in the information theory. The purpose of this paper is to present new bounds for relative entropy $D(p||q)$ of two probability distributions
Pantelimon G. Popescu, Sever S. Dragomir, Emil I. Slusanschi, Octavian N. Stanasila   +3 more
doaj  

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

Information theoretical approach to detecting quantum gravitational corrections

Journal of High Energy Physics
In this paper, we investigate the scales at which quantum gravitational corrections can be detected in a black hole using information theory. This is done by calculating the Kullback-Leibler divergence for the probability distributions obtained from the ...
Behnam Pourhassan, Xiaoping Shi, Salman Sajad Wani, Saif-Al-Khawari, Farideh Kazemian, İzzet Sakallı, Naveed Ahmad Shah, Mir Faizal   +7 more
doaj   +1 more source

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

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