Correlation heatmap of the principal components. by Muhammad Hilal Alkhudaydi (21560690)

“…For this reason, having a solid understanding of the elements responsible for these uncertainties is absolutely necessary. …”

Identification of Neuronal Activity from Extracelullar Recordings with Ground-truth Patch Clamp by Carina Germer (18692413)

Spatial patterns of the CAPs estimated from both splits are reproducible and strongly correlated with at least one of the basis CAPs. by Kangjoo Lee (11648345)

Data Sheet 1_MetaboLINK is a novel algorithm for unveiling cell-specific metabolic pathways in longitudinal datasets.csv by Jared Lichtarge (20548571)

“…For the first time, we applied the PCA-GLASSO algorithm (i.e., MetaboLINK) to metabolomics data derived from Nuclear Magnetic Resonance (NMR) spectroscopy performed on neural cells at various developmental stages, from human embryonic stem cells to neurons.…”

Video 2_Replicating associative learning of rodents with a neuromorphic robot in an open-field arena.mp4 by Tianze Liu (13922196)

Video 1_Replicating associative learning of rodents with a neuromorphic robot in an open-field arena.mp4 by Tianze Liu (13922196)

EEG Signals for Robust Cognitive Workload Recognition Under Noisy Conditions.zip by Fariya Bintay Shafi (21692408)

iNCog-EEG (ideal vs. Noisy Cognitive EEG for Workload Assessment) Dataset by Fariya Bintay Shafi (21692408)

The code for sample size calculation. by Ying Zhou (25031)

“…We collected basic clinical data and multimodal ultrasound data from these patients as predictive features, with clinical pregnancy as the predictive label, for model training. …”

Mpox Narrative on Instagram: A Labeled Multilingual Dataset of Instagram Posts on Mpox for Sentiment, Hate Speech, and Anxiety Analysis by Nirmalya Thakur (18869896)

LSTM model’s equations. by Songsong Wang (8088293)

“…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…”

Parameter’s interpretation. by Songsong Wang (8088293)

“…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…”

The models’ training parameters. by Songsong Wang (8088293)

“…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…”

Model’s measure methods. by Songsong Wang (8088293)

“…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…”

Association point and relationship. by Songsong Wang (8088293)

“…The findings indicate that the LSTM model, when integrated with the watershed-internal KG and LLM, can effectively incorporate critical elements influencing water level changes, the accuracy of the LLM-KG-LSTM model is enhanced by 3% compared to the standard LSTM model, and the LSTM series outperforms both RNN and GRU models, Our method will guide future research from the perspective of focusing on forecasting algorithms to the perspective of focusing on the relationship between multi-dimensional disaster data and algorithm parallelism.…”

Periodic Table’s Properties Using Unsupervised Chemometric Methods: Undergraduate Analytical Chemistry Laboratory Exercise by Adrian Gabriel Pereira de Quental (20382423)

“…The unsupervised algorithms were able to find “natural” clustering from the periodic table using the data structure without any prior knowledge of the class assignment of the samples. …”

Periodic Table’s Properties Using Unsupervised Chemometric Methods: Undergraduate Analytical Chemistry Laboratory Exercise by Adrian Gabriel Pereira de Quental (20382423)

“…The unsupervised algorithms were able to find “natural” clustering from the periodic table using the data structure without any prior knowledge of the class assignment of the samples. …”

Increasing overlap between H2AK119ub peak regions and activating modifications in the late cerebellum. by Aditya Parmar (22331873)

Neurodevelopmental enrichment of H3K27me1 within gene bodies. by Aditya Parmar (22331873)

CS activities to cues and their correlations with reward and sensorimotor variables. by Huu Hoang (9188747)