Results 81 to 90 of about 46,112 (290)

Inverse Design of Amorphous Materials With Targeted Properties

Advanced Materials, EarlyView.
AMDEN is a diffusion model framework for the inverse design of amorphous materials with targeted properties. By incorporating Hamiltonian Monte Carlo refinement into the denoising process, the framework overcomes the challenge of generating thermally relaxed disordered structures.
Jonas A. Finkler, Yan Lin, Tao Du, Jilin Hu, Morten M. Smedskjaer   +4 more
wiley   +1 more source

Controlled beam search for neural machine translation using subword units leveraging phrase-based statistical machine translation outputs

Discover Computing
The decoding phase is a crucial component in machine translation systems, alongside the creation of the model. Beam search is the most commonly used algorithm for decoding in these systems.
Emre Satir, Hasan Bulut
doaj   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Efficient position decoding methods based on fluorescence calcium imaging in the mouse hippocampus

, 2020
Large-scale fluorescence calcium imaging methods have become widely adopted for studies of long-term hippocampal and cortical neuronal dynamics. Pyramidal neurons of the rodent hippocampus show spatial tuning in freely foraging or head-fixed navigation ...
Tu, Mengyu, Gan, Wen-Biao, Chen, Zhe S., Adler, Avital, Zhao, Ruohe   +4 more
core   +1 more source

Weaving Intelligence: Thermally Drawn Multimaterial Fibers Toward AI‐Enabled Smart Textiles

Advanced Materials, EarlyView.
Thermally drawn multimaterial fibers are rapidly advancing as intelligent structural units for next‐generation smart textiles. Integrating multimaterial architectures with neuromorphic and spiking‐neural‐network principles enables fabrics that can sense, compute, and adapt autonomously.
Vuong Dinh Trung, Jiaxiang Yi, Hieu Nguyen‐Duc, Tien Nu Hoang Lo, Weili Zhao, Chaoqun Dong, Fabien Sorin, Baris Caglar, Lei Wei, Tung Nguyen‐Dang   +9 more
wiley   +1 more source

Benchmarking of hardware-efficient real-time neural decoding in brain–computer interfaces

Neuromorphic Computing and Engineering
Designing processors for implantable closed-loop neuromodulation systems presents a formidable challenge owing to the constrained operational environment, which requires low latency and high energy efficacy.
Paul Hueber, Guangzhi Tang, Manolis Sifalakis, Hua-Peng Liaw, Aurora Micheli, Nergis Tomen, Yao-Hong Liu   +6 more
doaj   +1 more source

Neural Encoding and Decoding at Scale

CoRR
Recent work has demonstrated that large-scale, multi-animal models are powerful tools for characterizing the relationship between neural activity and behavior. Current large-scale approaches, however, focus exclusively on either predicting neural activity from behavior (encoding) or predicting behavior from neural activity (decoding), limiting their ...
Yizi Zhang, Yanchen Wang, Mehdi Azabou, Alexandre Andre, Zixuan Wang, Hanrui Lyu, International Brain Laboratory, Eva L. Dyer, Liam Paninski, Cole L. Hurwitz   +9 more
openaire   +3 more sources

Dimensionality reduction for neural population decoding

, 2021
Rapidly developing technology for large scale neural recordings has allowed researchers to measure the activity of hundreds to thousands of neurons at single cell resolution in vivo.
Heller, C. ; https://orcid.org/, David, S.   +1 more
core   +1 more source

Deep Learning Inverse Design of Phase‐Change Reconfigurable Terahertz Metadevices for Multidimensional Secure Communication

Advanced Materials, EarlyView.
A deep learning inverse‐design framework is established to create versatile reconfigurable terahertz metadevices. By synergizing deep learning with phase‐change materials, this approach enables on‐demand customization of multidimensional electromagnetic responses.
Yisheng Dong, Xieyu Chen, Aarthy Nagarajan, Yi Yang, Zhihao Wang, Rui Yu, Chuang Zheng, Chunmei Ouyang, Xueqian Zhang, Tun Cao, Ranjan Singh, Zhen Tian   +11 more
wiley   +1 more source

On the Interpretability of Neural Network Decoders

Advanced Quantum Technologies
Abstract Neural‐network (NN) based decoders are becoming increasingly popular in the field of quantum error correction (QEC), including for decoding of state‐of‐the‐art quantum computation experiments. In this work, established interpretability methods are used from the field of machine learning, to introduce a toolbox to achieve an ...
Bödeker, Lukas, Kusters, Luc J. B., Müller, Markus   +2 more
openaire   +4 more sources