Quantum Machine Learning
4,297 papers
Quantum Machine Learning Research Context
This category covers quantum machine learning research, including quantum kernels, variational classifiers, hybrid learning systems, generative models, and QML benchmarks.
Showing 229-240 of 4,297
BEYOND THE PANDEMIC: LIFE POST COVID-19 THROUGH LOSS, GRIEF AND ADJUSTMENT
ZHEN FOONG RAYMOND FOO, IAN SHEN GOH, JANAK ASHOK TECKWANI, MAHPARA REYAZ KHAN, AHMAD MUSTAQIM YUSOFF, ZAINAH AHMAD ZAMANI
Bioinspired Neuromorphic Pressure Sensor with Ultra-Broad Range and High Sensitivity for Intelligent Flexible Electronics.
Yuan J, Yang F, Wang J, Qu Y, Guo D, Ning Z, Zong S, Li Y
Bioorthogonal modular assembly of functionalized nanobodies: A universal SNAP-click strategy for developing multiplex AFB1 detection platforms.
Liu C, Luo C, Zhang Y, Gong T, Bi M, Chen K, Niu W, Zheng H, Mao Y, Hou J, Lu Z, Sun T, Li X
Block-QAOA-Aware Detection with Parameter Transfer for Large-Scale MIMO
Shuai Zeng
Blockchain-Enabled Secure Signature Scheme With Quantum Key Distribution for IoMT-Based Healthcare Systems.
Prajapat S, Gautam D, Kumar P, Das AK, Pal S, Dong C
Boltzmann Attention: Learnable Ising Couplings for Cooperative Attention
Gilhan Kim, Daniel K. Park
Boltzmann sampling by diabatic quantum annealing
Anonymous
Boosting Computational Catalysis and Chemical Reactivity with Artificial Intelligence.
Vogiatzis KD, Corminboeuf C, Nova A, Jorner K, Kästner J, Meuwly M, Schwaller P, Böttcher V, Drosou M, Fako E, Hoppe H, Ivkovic Z, Iwanojko N, Pantazis DA, Schmid SP, Szenes K, Tetenoire A, Reiher M
Brain tumor segmentation and classification using an attention-based quantum U-Net framework
Rakib Hossain, Mujtahid Alam, Shuhena Salam Aonty
Brain-inspired quantum machine learning architecture and its benchmarking on astronomical classification
Subhash S. Pandey, Mousam Mondal, Xing Liang, Christos Kalyvas, Dimitrios Makris, Hongwei Wu
Breaking concentration barriers for quantum extreme learning on digital quantum processors
Timothée Dao, Ege Yilmaz, Ibrahim Shehzad, Christophe Pere, Kumar Ghosh, Isabelle Wittmann, Thomas Brunschwiler, Giorgio Cortiana, Corey O'Meara, Stefan Woerner, Francesco Tacchino
Bridging interpretable machine learning and large language models through direct representative selection and prediction: a two-layer framework for quantitative-linguistic insight.
Shimazaki T, Tachikawa M