Results 111 to 120 of about 6,372,670 (283)

Machine learning for number theory: unsupervised learning with L-functions

There is a strong tradition of computation in number theory, with notable data-driven insights including the prime number theorem and the conjecture of Birch and Swinnerton-Dyer.
Oliver, T.
core   +1 more source

Enhancing Super‐Resolution Spatial Transcriptomics Data by Transfer Learning

Advanced Science, EarlyView.
SpotZoomer employs a transfer‐learning‐based strategy to enhance the resolution of Visium data by leveraging available high‐resolution priors. The resulting super‐resolved maps enable sharper delineation of cell boundaries and more precise inference of cell–cell communication patterns that would otherwise remain obscured at native resolution.
Xiaoyu Li, Lihua Zhang, Wenwen Min
wiley   +1 more source

Improving morphology induction by learning spelling rules [PDF]

, 2009
Unsupervised learning of morphology is an important task for human learners and in natural language processing systems. Previous systems focus on segmenting words into substrings (taking ⇒ tak.ing), but sometimes a segmentation-only analysis is ...
Naradowski, Jason, Goldwater, Sharon; id_orcid   +1 more
core  

Polydopamine Nanoparticle‐Mediated Precise Near‐Infrared Optical Stimulation for Cognitive Enhancement

Advanced Science, EarlyView.
Polydopamine nanoparticles enable a precise, non‐genetic, and transcranial neuromodulation strategy via near‐infrared photothermal stimulation. By activating TRPV1 channels, this approach specifically enhances hippocampal gamma oscillations, thereby rescuing spatial memory deficits in models of perioperative neurocognitive disorder.
Yan‐Bo Zhou, Qiong Xue, Su‐Xuan Hou, Ke‐Yao Zhang, Wei‐Tong Pan, Ting‐Ting Zeng, Yu‐Ge Wang, Daqing Ma, Chenguang Zhao, Pan‐Miao Liu, Jian‐Jun Yang   +10 more
wiley   +1 more source

Using unsupervised machine learning for fault identification in virtual machines [PDF]

, 2015
Self-healing systems promise operating cost reductions in large-scale computing environments through the automated detection of, and recovery from, faults. However, at present there appears to be little known empirical evidence comparing the different
Schneider, Christopher
core   +2 more sources

Unsupervised Segmentation of Object Manipulation Operations from Multimodal Input [PDF]

, 2011
Barchunova A, Moringen J, Großekathöfer U, et al. Unsupervised Segmentation of Object Manipulation Operations from Multimodal Input. In: Hammer B, Villmann T, eds. Machine Learning Reports. New Challenges in Neural Computation.
Großekathöfer, Ulf, Barchunova, Alexandra ; https://orcid.org/, Moringen, Jan, Janssen, Herbert, Ritter, Helge ; https://orcid.org/, Haschke, Robert ; https://orcid.org/, Villmann, Thomas, Wachsmuth, Sven ; https://orcid.org/, Hammer, Barbara   +8 more
core  

Aberrant GRP78 Phase Transition Sustains Endothelial IRE1α Signaling and Drives Blood–Brain Barrier Failure in Cerebral Amyloid Angiopathy

Advanced Science, EarlyView.
Vascular Aβ40 corrupts GRP78 phase behavior in brain endothelial cells, sustaining IRE1α–TRAF2–JNK signaling and driving apoptosis, tight junction loss, and blood–brain barrier failure in cerebral amyloid angiopathy. Pharmacological IRE1α inhibition restores vascular integrity, reduces leakage, and improves functional outcomes, revealing a targetable ...
Honglin Zheng, Qiang Li, Haiyang Luo, Yapei Yuan, Na Zhang, Yongting Lu, Suying Duan, Jieshi Zhong, Hang Zhang, Chenyang Liu, Yaochong Zhang, Wenzhuo Zhao, Yaxuan Song, Tuo Wang, Si Yan, Yapeng Li, Han Liu, Yuan Gao, Zongping Xia, Yuming Xu   +19 more
wiley   +1 more source

Efficient Unsupervised Deep Band Selection for Hyperspectral Imagery: A Comparative Study With Mamba-Based Classification

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing
Band selection is a critical step in processing hyperspectral imagery (HSI); reducing input dimensionality allows models to mitigate redundancy, enhance computational efficiency, and improve learning accuracy.
Jacqueline Liu, Kara Combs, Jayson Boubin   +2 more
doaj   +1 more source

Deep‐Learning‐Driven High‐Fidelity In Vivo Hyperspectral Fluorescence Imaging Under Extreme Photon‐Limited Conditions

Advanced Science, EarlyView.
Highly overlapping fluorescent signals become distinguishable in photon‐limited living organisms via advanced imaging with intelligent reconstruction. The resulting in vivo hyperspectral imaging capability reveals nanoplastic uptake and circulation in live zebrafish, providing a new approach for studying complex biological and environmental processes ...
Renjian Li, Shutao Wu, Kaixiang Li, Zhenyu An, Yuwen Ben, Guiye LI, Sunil Kumar, James Mcginty, Tawfique Hasan, Songnian Fu, Meng Zhang, LingLing Chen   +11 more
wiley   +1 more source

ICOS‐ImmunoPET Monitors T Cell Activation After Combination Immune Checkpoint Blockade in a Mouse Model of Melanoma Brain Metastasis

Advanced Science, EarlyView.
ICOS‐immunoPET noninvasively visualizes activated T cells in melanoma brain metastases following combined anti‐PD‐1/anti‐CTLA‐4 therapy. Clinical translation of this imaging approach may improve patient stratification and treatment monitoring and serve as a quantitative imaging endpoint to support immunotherapy development and clinical trials in brain ...
Renesmee C. Kuo, Rohit Verma, Sydney C. Nagy, Mausam Kalita, Samuel Aubert, Josué Ballesteros‐Álvarez, Pedro Machado Almeida, Hannes Vogel, Israt S. Alam, Michael Lim, Michelle L. James   +10 more
wiley   +1 more source