Supplementary file 6_Learning Gaussian graphical models from correlated data.tiff by Zeyuan Song (13846951)

“…In this paper, we propose a cluster-based bootstrap algorithm to infer GGMs from correlated data. …”

Supplementary file 2_Learning Gaussian graphical models from correlated data.tiff by Zeyuan Song (13846951)

“…In this paper, we propose a cluster-based bootstrap algorithm to infer GGMs from correlated data. …”

Supplementary file 3_Learning Gaussian graphical models from correlated data.tiff by Zeyuan Song (13846951)

“…In this paper, we propose a cluster-based bootstrap algorithm to infer GGMs from correlated data. …”

Image 1_Learning Gaussian graphical models from correlated data.tiff by Zeyuan Song (13846951)

“…In this paper, we propose a cluster-based bootstrap algorithm to infer GGMs from correlated data. …”

Image 2_Learning Gaussian graphical models from correlated data.tiff by Zeyuan Song (13846951)

“…In this paper, we propose a cluster-based bootstrap algorithm to infer GGMs from correlated data. …”

High-Performance, High-Angular-Momentum J Engine on Graphics Processing Units by Elise Palethorpe (18126804)

“…Efficient evaluation of electron repulsion integrals (ERIs) involving high-angular-momentum Gaussian basis functions is computationally challenging on graphical processing units (GPUs), as traditional recurrence-based integral algorithms generate numerous intermediates, causing significant register pressure and memory bottlenecks. …”

Example of ray tracing to evaluate the length of the next step in the approximate random walk based on Patankar scheme: starting from the current location, two rays are drawn in th... by Loris Ibarrart (15195203)

Appendices: Reportable Serious Game Mechanics (SGMX): an ontological framework for the analysis and design of digital game-based learning (Vol. 2) by Glen Shearer (9834266)

Subjects: “…Distributed systems and algorithms…”

Stage 3 Workshops: Investigating the Learning Mechanics - Game Mechanics (LM-GM) model for the development of digital game-based learning by Glen Shearer (9834266)

Subjects: “…Distributed systems and algorithms…”

Additional file 3 of Nanomaterial isolated extracellular vesicles enable high precision identification of tumor biomarkers for pancreatic cancer liquid biopsy by Zachary F. Greenberg (21642724)

Additional file 2 of Nanomaterial isolated extracellular vesicles enable high precision identification of tumor biomarkers for pancreatic cancer liquid biopsy by Zachary F. Greenberg (21642724)

Mosaic dataset augmentation. by Kangning Li (6069629)

“…Secondly, in terms of feature fusion, a Bidirectional Feature Pyramid Network (BiFPN) is added to the original neck of YOLOv5 to enhance the fusion ability of shallow graphic features and deep semantic features. Finally, the performance of the improved YOLOv5 algorithm is validated through ablation experiments and comparative experiments with other defect detection algorithms, including the Small_obj algorithm the existing method of adding a small target detection head for identifying small target defects. …”

Three types of loss curves. by Kangning Li (6069629)

“…Secondly, in terms of feature fusion, a Bidirectional Feature Pyramid Network (BiFPN) is added to the original neck of YOLOv5 to enhance the fusion ability of shallow graphic features and deep semantic features. Finally, the performance of the improved YOLOv5 algorithm is validated through ablation experiments and comparative experiments with other defect detection algorithms, including the Small_obj algorithm the existing method of adding a small target detection head for identifying small target defects. …”

The structure of the Res2Block module. by Kangning Li (6069629)

“…Secondly, in terms of feature fusion, a Bidirectional Feature Pyramid Network (BiFPN) is added to the original neck of YOLOv5 to enhance the fusion ability of shallow graphic features and deep semantic features. Finally, the performance of the improved YOLOv5 algorithm is validated through ablation experiments and comparative experiments with other defect detection algorithms, including the Small_obj algorithm the existing method of adding a small target detection head for identifying small target defects. …”

The structure of the BiFPN. by Kangning Li (6069629)

“…Secondly, in terms of feature fusion, a Bidirectional Feature Pyramid Network (BiFPN) is added to the original neck of YOLOv5 to enhance the fusion ability of shallow graphic features and deep semantic features. Finally, the performance of the improved YOLOv5 algorithm is validated through ablation experiments and comparative experiments with other defect detection algorithms, including the Small_obj algorithm the existing method of adding a small target detection head for identifying small target defects. …”

Randomly adding Gaussian white noise. by Kangning Li (6069629)

“…Secondly, in terms of feature fusion, a Bidirectional Feature Pyramid Network (BiFPN) is added to the original neck of YOLOv5 to enhance the fusion ability of shallow graphic features and deep semantic features. Finally, the performance of the improved YOLOv5 algorithm is validated through ablation experiments and comparative experiments with other defect detection algorithms, including the Small_obj algorithm the existing method of adding a small target detection head for identifying small target defects. …”

Hybrid-based food recommender system utilizing KNN and SVD approaches by Zhi-Toung Yap (20381433)

“…Besides that, this paper will discuss the combination of various algorithms: collaborative filtering, content-based filtering, and hybrid approaches. …”

Data Sheet 1_Flow-based parameterization for DAG and feature discovery in scientific multimodal data.pdf by Elise Walker (19937997)

Monitoring and Diagnosis for Multi-Mode Processes with Varying Operating Parameters: A Covariate-Adjusted Mixture Bayesian Network Approach by Yujie Wei (1502143)

Example of downstream analysis. by Yukako Yamane (9034133)