Results 131 to 140 of about 476,790 (313)
Molecular set representation learning
Computational representation of molecules can take many forms, including graphs, string-encodings of graphs, binary vectors, or learned embeddings in the form of real-valued vectors.
Pierre, Vandergheynst +2 more
core +1 more source
Reinforcement learning in populations of spiking neurons
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
Clustering Algorithm Reveals Dopamine‐Motor Mismatch in Cognitively Preserved Parkinson's Disease
ABSTRACT Objective To explore the relationship between dopaminergic denervation and motor impairment in two de novo Parkinson's disease (PD) cohorts. Methods n = 249 PD patients from Parkinson's Progression Markers Initiative (PPMI) and n = 84 from an external clinical cohort.
Rachele Malito +14 more
wiley +1 more source
ABSTRACT Introduction Progressive Supranuclear Palsy (PSP) is a neurodegenerative ‘tauopathy’ with predominating pathology in the basal ganglia and midbrain. Caudal tau spread frequently implicates the cerebellum; however, the pattern of atrophy remains equivocal.
Chloe Spiegel +8 more
wiley +1 more source
This quantitative study aims to examine the influence of the learning environment on students’ mathematical representation abilities. The research is motivated by the relatively low levels of mathematical representation skills observed among students ...
Nurma Izzati +2 more
doaj +1 more source
Evaluating Representation Learning on the Protein Structure Universe [PDF]
We introduce ProteinWorkshop, a comprehensive benchmark suite for representation learning on protein structures with Geometric Graph Neural Networks. We consider large-scale pre-training and downstream tasks on both experimental and predicted structures ...
Morehead A. +10 more
core
Geometric Multimodal Contrastive Representation Learning
Learning representations of multimodal data that are both informative and robust to missing modalities at test time remains a challenging problem due to the inherent heterogeneity of data obtained from different channels.
Poklukar, Petra, +5 more
core
CX3CL1 in Early Detection of Alzheimer's Disease: Plasma Dynamics Across Age and Disease Stages
ABSTRACT Backgrounds Alzheimer's disease (AD) is characterized by amyloid‐beta plaques, tau tangles, and neuroinflammation. C‐X3‐C motif chemokine ligand 1 (CX3CL1, also known as fractalkine), a neuroimmune chemokine implicated in AD pathogenesis, shows inconsistent alterations in plasma/serum across studies.
Ling Wang +6 more
wiley +1 more source
Value of MRI Outcomes for Preventive and Early‐Stage Trials in Spinocerebellar Ataxias 1 and 3
ABSTRACT Objective To examine the value of MRI outcomes as endpoints for preventive and early‐stage trials of two polyglutamine spinocerebellar ataxias (SCAs). Methods A cohort of 100 participants (23 SCA1, 63 SCA3, median Scale for the Assessment and Rating of Ataxia (SARA) score = 5, 42% preataxic, and 14 gene‐negative controls) was scanned at 3T up ...
Thiago J. R. Rezende +26 more
wiley +1 more source
Stable and Efficient Representation Learning with Nonnegativity Constraints [PDF]
Orthogonal matching pursuit (OMP) is an efficient approximation algorithm for computing sparse representations. However, prior research has shown that the representations computed by OMP may be of inferior quality, as they deliver suboptimal ...
Lin, Tsung-Han, Kung, H.
core

