Results 101 to 110 of about 1,579,753 (313)
PAL – parallel active learning for machine-learned potentials
Digital DiscoveryAn automated, modular, and parallel active learning (PAL) library that integrates AL tasks and manages their execution and communication on shared- and distributed-memory systems using the Message Passing Interface (MPI).
Chen Zhou +7 more
openaire +4 more sources
Directed evolution of enzymes at the crossroads of tradition and innovation
FEBS Open Bio, EarlyView.An iterative cycle of data‐driven enzyme optimization comprising four stages: genetic diversification of a template enzyme, expression of protein variants, high‐throughput evaluation, and machine‐learning‐guided redesign of the next variant library.
Maria Tomkova +2 more
wiley +1 more source
Reinforcement learning in populations of spiking neurons
, 2008 Population coding is widely regarded as a key mechanism for achieving reliable behavioral responses in the face of neuronal variability. But in standard reinforcement learning a flip-side becomes apparent.
Urbanczik, R +3 more
core +1 more source
Tracking patterns in self-regulated learning using students’ self-reports and online trace data [PDF]
, 2020 For decades, self-report instruments – which rely heavily on students’ perceptions and beliefs – have been the dominant way of measuring motivation and strategy use.
Van Klaveren, Chris; id_orcid +9 more
core +1 more source
FEBS Open Bio, EarlyView.The cytoskeleton‐mediated transport of mitochondria via tunnelling nanotubes restores respiration, increases ATP production, rescues cells from apoptosis, activates the AKT/mTOR signalling pathway, promotes cell migration and invasiveness, contributes to cancer progression and treatment resistance.
Stanislava Martínková, Jan Trnka
wiley +1 more source
Machine-learned potentials for solvation modeling
Journal of Physics: Condensed MatterAbstract Solvent environments play a central role in determining molecular structure, energetics, reactivity, and interfacial phenomena. However, modeling solvation from first principles remains difficult due to the complex interplay of interactions and unfavorable computational scaling of first-principles treatment with system size ...
Roopshree Banchode +3 more
openaire +3 more sources
Pathways and pitfalls: a qualitative study of student experiences in biomedical science education
FEBS Open Bio, EarlyView.Biomedical science students from underrepresented backgrounds face barriers including financial strain, disrupted laboratory access and cultural exclusion. Peer networks provide vital support when institutional systems are difficult to navigate. To create inclusive learning environments and achieve academic success, educators should blend active, hands‐
Olivia J. Russell +8 more
wiley +1 more source
Long‐Term Follow‐Up of Chemotherapy‐Associated Biological Aging in Women With Early Breast Cancer
Aging and Cancer, EarlyView.Women threated with adjuvant chemotherapy for early breast cancer have sustained long‐term increase in p16INK4a,, a robust marker of cell senescence, suggesting a chemotherapy‐associated age acceleration. p16INK4a as well as other biomarkers may identify patients at greatest risk for senescence‐related diseases of aging.
Hyman B. Muss +12 more
wiley +1 more source
Curriculum reinforcement learning via constrained optimal transport
, 2022 Curriculum reinforcement learning (CRL) allows solving complex tasks by generating a tailored sequence of learning tasks, starting from easy ones and subsequently increasing their difficulty.
Klink, Pascal +4 more
core
Improving Bayesian Network Structure Learning in the Presence of Measurement Error
, 2022 Structure learning algorithms that learn the graph of a Bayesian network from observational data often do so by assuming the data correctly reflect the true distribution of the variables.
Liu, Y, Constantinou, AC, Guo, Z
core +1 more source