Results 91 to 100 of about 221,770 (298)

Domain robustness in neural machine translation

, 2019
Translating text that diverges from the training domain is a key challenge for machine translation. Domain robustness---the generalization of models to unseen test domains---is low for both statistical (SMT) and neural machine translation (NMT). In this paper, we study the performance of SMT and NMT models on out-of-domain test sets.
Müller, Mathias, Rios, Annette, Sennrich, Rico   +2 more
openaire   +5 more sources

Beyond Order: Perspectives on Leveraging Machine Learning for Disordered Materials

Advanced Engineering Materials, EarlyView.
This article explores how machine learning (ML) revolutionizes the study and design of disordered materials by uncovering hidden patterns, predicting properties, and optimizing multiscale structures. It highlights key advancements, including generative models, graph neural networks, and hybrid ML‐physics methods, addressing challenges like data ...
Hamidreza Yazdani Sarvestani, Surabhi Nadigotti, Erfan Fatehi, Derek Aranguren van Egmond, Behnam Ashrafi   +4 more
wiley   +1 more source

3D (Bio) Printing Combined Fiber Fabrication Methods for Tissue Engineering Applications: Possibilities and Limitations

Advanced Functional Materials, EarlyView.
Biofabrication aims at providing innovative technologies and tools for the fabrication of tissue‐like constructs for tissue engineering and regenerative medicine applications. By integrating multiple biofabrication technologies, such as 3D (bio) printing with fiber fabrication methods, it would be more realistic to reconstruct native tissue's ...
Waseem Kitana, Indra Apsite, Leonid Ionov   +2 more
wiley   +1 more source

Machine Translation Indonesian Bengkulu Malay Using Neural Machine Translation-LSTM

IJCCS (Indonesian Journal of Computing and Cybernetics Systems)
The machine translator is an application in Natural Language Processing (NLP) that focuses on translating between languages. Several previous research have used Statistical Machine Translation (SMT) with a parallel corpus of Indonesian and Bengkulu Malay
Bella Okta Sari Miranda, Herman Yuliansyah, Muhammad Kunta Biddinika   +2 more
doaj   +1 more source

Machine Learning‐Enabled Polymer Discovery for Enhanced Pulmonary siRNA Delivery

Advanced Functional Materials, EarlyView.
This study provides an efficient approach to train a machine learning model by merging heterogeneous literature data to predict suitable polymers for siRNA delivery. Without the need for extensive laboratory synthesis, the machine learning enabled a virtual screening and successfully predicted a polymer that is validated for effective gene silencing in
Felix Sieber‐Schäfer, Min Jiang, Adrian Kromer, Anny Nguyen, Müge Molbay, Simone Pinto Carneiro, David Jürgens, Gerald Burgstaller, Bastian Popper, Benjamin Winkeljann, Olivia Monika Merkel   +10 more
wiley   +1 more source

Investigating Backtranslation in Neural Machine Translation

, 2018
This research has been supported by the ADAPT Centre for Digital Content Technology which is funded under the SFI Research Centres Programme (Grant 13/RC/2106) and is co-funded under the European Regional Development Fund. This work has also received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie ...
Poncelas, Alberto, Shterionov, Dimitar, Way, Andy, Maillette de Buy Wenniger, Gideon, Passban, Peyman   +4 more
openaire   +4 more sources

Eco‐Fabricated Nanowave‐Textured Implants Drive Microtubule‐Assisted Nuclear Mechanotransduction and Chromatin Modification: Biophysical Priming for Osteogenesis and Bone Regeneration

Advanced Functional Materials, EarlyView.
Eco‐friendly nanowave‐textured implants produced via femtosecond laser fabrication enhance bone regeneration by orchestrating a precise mechanotransduction cascade. This nanotopography directs mesenchymal stem cell alignment and cytoskeletal organization, triggering changes in nuclear shape and chromatin acetylation that prime cells for osteogenesis ...
Bosu Jeong, Ji‐Young Yoon, Junyong Ahn, Byunghak Lee, Sung‐Min Park, Jae‐Heon Kim, Buuvee Bayarkhangai, Yu Jin Kim, Sak Lee, Jonathan C. Knowles, Moon‐Young Kim, DongJun Lee, Sang‐Hoon Rhee, Hae‐Hyoung Lee, Hae‐Won Kim, Jung‐Hwan Lee   +15 more
wiley   +1 more source

Neural Machine Translation for Indian Languages

Journal of Intelligent Systems, 2019
Machine Translation bridges communication barriers and eases interaction among people having different linguistic backgrounds. Machine Translation mechanisms exploit a range of techniques and linguistic resources for translation prediction.
Pathak Amarnath, Pakray Partha
doaj   +1 more source

Binarized Neural Machine Translation

, 2023
The rapid scaling of language models is motivating research using low-bitwidth quantization. In this work, we propose a novel binarization technique for Transformers applied to machine translation (BMT), the first of its kind. We identify and address the problem of inflated dot-product variance when using one-bit weights and activations.
Zhang, Yichi, Garg, Ankush, Cao, Yuan, Lew, Łukasz, Ghorbani, Behrooz, Zhang, Zhiru, Firat, Orhan   +6 more
openaire   +2 more sources

Transducer Materials Mediated Deep Brain Stimulation in Neurological Disorders

Advanced Functional Materials, EarlyView.
This review discusses advanced transducer materials for improving deep brain stimulation (DBS) in neurological disorders. These materials respond to light, ultrasound, or magnetic fields, enabling precise, less invasive neuromodulation. Their stimulus‐responsive properties enhance neural control and adaptive therapy, paving the way for next‐generation ...
Di Zhao, Zhengyang Cao, Guangjun Zhong, Limin Shi, Junxia Xie, Jianhua Hao   +5 more
wiley   +1 more source