Modular architecture design of PyNoetic showing all its constituent functions. by Gursimran Singh (575288)

Subjects:

Listed python codes of our algorithm with explanations (Python 3.9 recommended). by Takayuki Niizato (162226)

Illustration of the unrestricted model and its training algorithm. by Yuru Song (21300760)

Overview of functionality supported by PyNoetic and its various modules, including the live analysis and programmable flowchart. by Gursimran Singh (575288)

Subjects:

Example of a network, its transition function, and its initial and desired states. by Mohammad Moradi (3642007)

Efficient algorithms to discover alterations with complementary functional association in cancer by Rebecca Sarto Basso (6728921)

“…In addition, our algorithms are much faster than the state-of-the-art, allowing the analysis of large datasets of thousands of target profiles from cancer cell lines. …”

Code snippets to add user-specific custom functionality in PyNoetic. by Gursimran Singh (575288)

Subjects:

Example of landmark registration to align ‘peaks’ of high density in the probability density function (PDF) of CD4 expression on blood T cells for a target distribution and chosen... by Ross J. Burton (10941910)

Completion times for different algorithms. by Jianbin Zheng (587000)

“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. The effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …”

The average cumulative reward of algorithms. by Jianbin Zheng (587000)

“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. The effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …”

Results of the application of different clustering algorithms to average functional connectivity from healthy subjects. by Francisco Páscoa dos Santos (16510676)

“…<p>A) Resulting cluster inertia from applying the k-means algorithm described in the methods to empirical averaged functional connectivity from healthy subjects, with different numbers of clusters. …”

Simulation settings of rMAPPO algorithm. by Jianbin Zheng (587000)

“…This paper first analyzes the H-beam processing flow and appropriately simplifies it, develops a reinforcement learning environment for multi-agent scheduling, and applies the rMAPPO algorithm to make scheduling decisions. The effectiveness of the proposed method is then verified on both the physical work cell for riveting and welding and its digital twin platform, and it is compared with other baseline multi-agent reinforcement learning methods (MAPPO, MADDPG, and MASAC). …”

WGCNA and machine learning algorithms. by Shushu Wang (6870191)

Flowchart of the specific incarnation of the BO algorithm used in the experiments. by Lisa Laux (9367681)

“…To choose the next pipeline configuration to evaluate, the BO algorithm uses an Expected Improvement function to trade off maximisation of QS with the need to fully learn the GP. …”

Adaptive H-REMD simulation algorithm. by Danial Pourjafar-Dehkordi (7165523)

Data_Sheet_1_Resting-State Functional Connectivity Estimated With Hierarchical Bayesian Diffuse Optical Tomography.docx by Takatsugu Aihara (4433524)

Subjects:

DataSheet1_Mathematical algorithm–based identification of the functional components and mechanisms in depression treatment: An example of Danggui-Shaoyao-San.docx by Wenxia Gong (13277883)

Subjects: “…Cell Biology…”

The GOR4 and SOPMA algorithm findings. by Ahmad Abdullah Mahdeen (19704401)

Flowchart of P&O-based MPPT algorithm. by Luqman Khan (17921419)

Brief sketch of the quasi-attraction/alignment algorithm. by Takayuki Niizato (162226)

“…The focal agent selects its next direction randomly based on . (D) A brief sketch of the avoidance algorithm. …”