Results 301 to 310 of about 12,455,841 (338)

Efficient structure learning of gene regulatory networks with Bayesian active learning. [PDF]

BMC Bioinformatics
Sándor D, Antal P.
europepmc   +1 more source

Bio‐Inspired Molecular Events in Poly(Ionic Liquids)

Advanced Functional Materials, EarlyView.
Originating from dipolar and polar inter‐ and intra‐chain interactions of the building blocks, the topologies and morphologies of poly(ionic liquids) (PIL) govern their nano‐ and micro‐processibility. Modulating the interactions of cation‐anion pairs with aliphatic dipolar components enables the tunability of properties, facilitated by “bottom‐up ...
Jiahui Liu, Marek W. Urban
wiley   +1 more source

Active learning-assisted directed evolution. [PDF]

Nat Commun
Yang J, Lal RG, Bowden JC, Astudillo R, Hameedi MA, Kaur S, Hill M, Yue Y, Arnold FH.   +8 more
europepmc   +1 more source

Proposal Writing Training and Idea Development for Early-Career Researchers Based on Constructive Alignment, Co-Creation and Active Learning Strategies. [PDF]

Ecol Evol
Hoffmann F, de Vareilles M, Chen L, Downy C, Goris N.   +4 more
europepmc   +1 more source

CABNas-nir: A near-infrared classification for urban pipe network sludge on the fusion algorithm of NAS framework and active learning. [PDF]

PLoS One
Yang Y, Fu L, Wei Q, Feng Y, Zhu L, Dai Y, Xiao W, Fan T, Jin X.   +8 more
europepmc   +1 more source

Simulations and active learning enable efficient identification of an experimentally-validated broad coronavirus inhibitor. [PDF]

Nat Commun
Elez K, Hempel T, Shrimp JH, Moor N, Raich L, Rocha C, Winter R, Le T, Pöhlmann S, Hoffmann M, Hall MD, Noé F.   +11 more
europepmc   +1 more source

Evidence-theory-based Reliability Analysis Method Using Active-learning Kriging Model

WEI Xinpeng, YAO Zhongyang, BAO Wenli, ZHANG Zhe, JIANG Chao   +4 more
openalex   +1 more source

Active learning algorithm for alleviating the user cold start problem of recommender systems. [PDF]

Sci Rep
De Pessemier T, Willems B, Martens L.
europepmc   +1 more source

Low-Complexity Machine Learning Models for Active Noise Control in Nonlinear Systems

Miguel Ferrer, María de Diego, Alberto Gonzalez   +2 more
openalex   +1 more source

DDSUD: dynamically detecting subsequence uncertainty and diversity for active learning in imbalanced Chinese sentiment analysis. [PDF]

PeerJ Comput Sci
Xiong S, Si Y, Zhang G, Wang B, Zheng G, Si H.   +5 more
europepmc   +1 more source