Results 51 to 60 of about 10,752 (214)

On the symmetrized S-divergence [PDF]

open access: yesITM 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

De Novo Design of Membrane‐Targeting Antimicrobial Peptides Against Gram‐Negative Bacteria Using a Generative Artificial Intelligence Framework

open access: yesAdvanced Science, EarlyView.
Antimicrobial resistance caused by Gram‐negative bacteria remains difficult to overcome due to the protective outer membrane. To address this challenge, a multi‐condition constrained generative AI framework, GenMTAMP is proposed for de novo membrane‐targeting antimicrobial peptide design by integrating physicochemical and spatial structure descriptors.
Jingxiao Yu   +5 more
wiley   +1 more source

Discriminator‐Guided Inverse Folding for Multi‐Property Protein Design

open access: yesAdvanced Science, EarlyView.
Discriminator‐Guided Inverse Folding (DGIF) integrates multiple property predictors trained from single‐property datasets to guide protein sequence generation from a backbone structure. DGIF enables simultaneous improvement of thermostability and solubility without requiring multi‐property annotated datasets and generates designs that move toward the ...
Yuchuan Zheng   +7 more
wiley   +1 more source

f-divergence Analysis of Generative Adversarial Network

open access: yesFoundations 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

Uniqueness and Optimality of Dynamical Extensions of Divergences

open access: yesPRX 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

SPADE: A Deep Learning Framework for Spatial Mapping and Quantitative Cell–Cell Interaction Inference

open access: yesAdvanced Science, EarlyView.
SPADE integrates spatial transcriptomics with single‐cell RNA sequencing by using cell–cell communications (CCC) as a guide for spatial mapping. It improves cell‐type localization, enhances sparse gene‐expression signals, and reveals CCC programs at single‐spot resolution.
Xinyi Li, Ning Zhang, Zijie Jin
wiley   +1 more source

Generalized Kullback-Leibler Divergence Loss

open access: yesIEEE Transactions on Pattern Analysis and Machine Intelligence
TPAMI 2026, extension of our NeurIPS paper "Decoupled Kullback-Leibler Divergence Loss".
Jiequan Cui   +7 more
openaire   +2 more sources

CauFinder: Steering Cell‐State and Phenotype Transitions by Causal Disentanglement Learning

open access: yesAdvanced Science, EarlyView.
CauFinder combines causal disentanglement modeling and network control to prioritize causal drivers of cell‐state transitions from observational transcriptomic data. The framework separates transition‐relevant signals from spurious associations, nominates intervention targets across biological and disease contexts, and identifies DAAM1 as an actionable
Chengming Zhang   +11 more
wiley   +1 more source

TSTScope Unifies Single‐Cell Multi‐Omics to Identify Functional T Cell States Predictive of Immunotherapy Response

open access: yesAdvanced Science, EarlyView.
TSTScope is an interpretable AI framework that integrates single‐cell transcriptomes with TCR information through curated gene‐program constraints. By linking receptor context to functional T cell states, it reveals response‐associated tumor‐specific T cell programs in lung cancer immunotherapy cohorts and defines an MPR score associated with ...
Shiwei Cao   +8 more
wiley   +1 more source

Information theoretical approach to detecting quantum gravitational corrections

open access: yesJournal 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   +7 more
doaj   +1 more source

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