Results 161 to 170 of about 11,006,319 (257)

Automating Chemical Reasoning in High‐Throughput Phase Identification With a Probabilistic, LLM‐Guided Framework

Advanced Science, EarlyView.
Autonomous laboratories can now synthesize materials faster than experts can interpret the resulting diffraction data. A probabilistic framework combines refinement‐fit metrics with large language model‐derived chemical reasoning to rank competing phase interpretations and flag those unsuitable for autonomous use.
Olympia Dartsi, Lauren N. Walters, Amalie E. Trewartha, Steven B. Torrisi, Amanda Volk, Liam Joyce, Gerbrand Ceder, Anubhav Jain   +7 more
wiley   +1 more source

Structure-conditioned self-supervised learning of residue interaction constraints in protein kinases for variant interpretation. [PDF]

Bioinformatics
Fadaei S, Krebs FS, Zoete V.
europepmc   +1 more source

Anisotropic Memristive Switching in NbOCl2 Enabled by Directional Oxygen Ion Migration

Advanced Science, EarlyView.
This study investigates strongly orientation‐dependent memristive switching in anisotropic NbOCl2, observed exclusively along the in‐plane c‐axis. The switching originates from direction‐selective oxygen‐ion migration and vacancy propagation that modulate the Pd/NbOCl2 Schottky barrier, enabling short‐term plasticity.
Caokun Wang, Yun Ji, Sanchali Mitra, Yufei Shi, Haofei Zheng, Yee Sin Ang, Kah‐Wee Ang   +6 more
wiley   +1 more source

Generalizable self-supervised learning for imaging flow cytometry on multi-dataset leukocyte differential. [PDF]

Microsyst Nanoeng
Huang X, Wang Z, Du X, Fang Z, Chen S, Chen Y, Wang J, Huo X, Wang K, Chen X, Zhang Y, Chen J.   +11 more
europepmc   +1 more source

A Generative Neuro‐Symbolic AI for Protein Sequence Design

Advanced Science, EarlyView.
We introduce EffieDes, a neuro‐symbolic framework coupling deep learning‐based fitness landscape parameterization with exact automated reasoning. Unlike greedy sampling, EffieDes identifies sequences that globally optimize fitness while satisfying intricate design constraints.
Marianne Defresne, Delphine Dessaux, Samuel Buchet, Lucie Barthe, Liza Ammar‐Khodja, Bessam Azizi, Valentin Durante, Gianluca Cioci, Simon de Givry, Alain Roussel, Luis F. Garcia‐Alles, Thomas Schiex, Sophie Barbe   +12 more
wiley   +1 more source

Strategy of Triple‐Gradient in Binary Pixels for Flexible Pressure Sensing with High Sensitivity and Wide‐Range Linearity

Advanced Science, EarlyView.
A flexible pressure sensor with triple‐gradient design of conductivity, modulus, and dimension in binary micro‐dome pixels is proposed. Based on precisely‐designed CNT/PDMS matrix, the device exhibits a linear sensitivity of 974.1 kPa−1 across range up to 1.8 MPa (R2 > 0.99), offering an effective strategy for potential applications in healthcare ...
Yifan Liu, Xiao Xu, Fengming Hu, Yuanzhe Liang, Zidong Yin, Biao Qi, Ruolin Liu, Ziyi Dai, Jianyi Luo, Bingpu Zhou   +9 more
wiley   +1 more source

Physics-guided self-supervised learning for high-fidelity reconstruction in live-cell imaging. [PDF]

Npj Imaging
Xu G, Li X, Chen X.
europepmc   +1 more source

Multitask Deep Learning Model for Predicting Lymph Node Metastasis and Disease‐Free Survival From Cytology Images in Bladder Cancer: A Multicenter Study With Pan‐Cytology Validation

Advanced Science, EarlyView.
Through self‐supervised pretraining and supervised fine‐tuning on large‐scale cytology image datasets, CytoNet predicts lymph node metastasis and survival. Across independent cohorts, this multitask framework demonstrates robust performance, improves risk stratification beyond radiological assessment, and provides interpretable evidence to support ...
Guibin Hong, Fan Jiang, Ye Xie, Xiaowei Huang, Runnan Shen, Yun Wang, Mengyi Zhu, Haoxuan Wang, Hongkun Yang, Yanxiao Nie, Zhen Lin, Rui Chen, Nengtai Ouyang, Tianxin Lin, Shaoxu Wu   +14 more
wiley   +1 more source

[W3D3] Un/Self-supervised learning methods

Week 3, Day 3: Unsupervised and self-supervised learning By Neuromatch ...
Konstantine Tsafatinos, Jiaxin Cindy Tu
core  

Advancing human-centric AI for robust X-ray analysis through holistic self-supervised learning. [PDF]

Nat Commun
Moutakanni T, Bojanowski P, Chassagnon G, Hudelot C, Joulin A, LeCun Y, Muckley M, Oquab M, Revel MP, Vakalopoulou M.   +9 more
europepmc   +1 more source