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Deposit, archive and share your final research data in DR-NTU (Data)

DR-NTU (Data) is for research data deposit. For research paper deposits, please use DR-NTU.

Mission: DR-NTU (Data) curates, stores, preserves, makes available and enables the download of digital data generated by the NTU research community. The repository develops and provides guidance for managing, sharing, and reusing research data to promote responsible data sharing in support of open science and research integrity.

Who can deposit? NTU faculty, research staff and students.

What can be deposited? Final, non-sensitive research data from projects carried out at NTU. The uploaded content must not infringe upon the copyrights or other intellectual property rights, and must be void of all identifiable information.

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1 to 10 of 3,356 Results
Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations.
Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations.
Apr 9, 2026 - Rafika RAHMAWATI
Rahmawati, Rafika; Li, Shuzhou, 2026, "Benchmarking adaptive circuits and quantum natural gradients variational quantum algorithm (VQE) for efficient molecular simulations.", https://doi.org/10.21979/N9/LDPUKT, DR-NTU (Data), V2
The provided data includes the general source code and its computational results.
Replication Data for: Christian Nationalism and Its Influence on Mass Attitudes toward Democracy
Apr 9, 2026 - Muhamad Yusri Bin MOHAMED SUPIYAN
Mohamed Supiyan, Muhamad Yusri Bin, 2026, "Replication Data for: Christian Nationalism and Its Influence on Mass Attitudes toward Democracy", https://doi.org/10.21979/N9/DC5OSX, DR-NTU (Data), V1
This is the CSV file data for replication purposes for "Christian Nationalism and Its Influence on Mass Attitudes toward Democracy."
Muhamad Yusri Bin MOHAMED SUPIYAN(Nanyang Technological University)
Apr 9, 2026School of Social Sciences (SSS)
Geochemical dataset for the paper "Large caldera eruptions fueled by long‑lived basaltic roots"
Apr 9, 2026 - Large caldera eruptions fueled by long‑lived basaltic roots
Mourey, Adrien Jean Jacques, 2026, "Geochemical dataset for the paper "Large caldera eruptions fueled by long‑lived basaltic roots"", https://doi.org/10.21979/N9/KES9SY, DR-NTU (Data), V1, UNF:6:a+h7nKZc2molg1zeN0YfjQ== [fileUNF]
Geochemical data used in the study "Large caldera eruptions fueled by long‑lived basaltic roots" by Mourey et al.
Large caldera eruptions fueled by long‑lived basaltic roots(Nanyang Technological University)
Apr 9, 2026Adrien Jean Jacques MOUREY
This supplementary dataset supports the paper “Large caldera eruptions fueled by long-lived basaltic roots” by Adrien J. Mourey et al. It includes: (1) sample information and mineral modes; (2) diffusion times; (3) plagioclase major- and trace-element transects; (4) major-element...
Other Projects of the Liu Team(Nanyang Technological University)
Apr 9, 2026LIU Weichen
Rafika RAHMAWATI (Nanyang Technological University)
Apr 8, 2026School of Materials Science and Engineering (MSE)
Data for Tier 1 Project
Replication Data for: Conformer-Resolved Ultrafast Chemical Dynamics Observed at Ambient Temperature
Apr 7, 2026 - LOH Zhi Heng
Wei, Zhengrong; González Vázquez, Jesús; Recio, Pedro; García, Gustavo; Marggi Poullain, Sonia; Li, Jialin; Bañares, Luis; Loh, Zhi Heng, 2026, "Replication Data for: Conformer-Resolved Ultrafast Chemical Dynamics Observed at Ambient Temperature", https://doi.org/10.21979/N9/JAHVZC, DR-NTU (Data), V1
Replication Data for: Conformer-Resolved Ultrafast Chemical Dynamics Observed at Ambient Temperature
Replication Data for: Exploring Deep-to-Shallow Transformable Neural Networks for Intelligent Embedded Systems
Apr 7, 2026 - Luo Xiangzhong
Luo, Xiangzhong; Liu, Weichen, 2026, "Replication Data for: Exploring Deep-to-Shallow Transformable Neural Networks for Intelligent Embedded Systems", https://doi.org/10.21979/N9/VVAKSR, DR-NTU (Data), V1
The dataset includes the source codes and readme file for implementing the design presented in the paper "Exploring Deep-to-Shallow Transformable Neural Networks for Intelligent Embedded Systems", accepted by IEEE Transactions on Computer-Aided Design of Integrated Circuits and S...
Replication Data for: Double-Win NAS: Towards Deep-to-Shallow Transformable Neural Architecture Search for Intelligent Embedded Systems
Apr 7, 2026 - Luo Xiangzhong
Luo, Xiangzhong; Liu, Di; Kong, Hao; Huai, Shuo; Liu, Weichen, 2026, "Replication Data for: Double-Win NAS: Towards Deep-to-Shallow Transformable Neural Architecture Search for Intelligent Embedded Systems", https://doi.org/10.21979/N9/BIOGHZ, DR-NTU (Data), V1
The dataset includes the source codes and readme file for implementing the design presented in the paper "Double-Win NAS: Towards Deep-to-Shallow Transformable Neural Architecture Search for Intelligent Embedded Systems"
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