Victor Adeyi Odeh
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View article: Simplicity vs. Complexity in Time Series Forecasting: A Comparative Study of iTransformer Variants
Simplicity vs. Complexity in Time Series Forecasting: A Comparative Study of iTransformer Variants Open
View article: Simplicity vs. Complexity in time series forecasting: a comparative study of iTransformer variants
Simplicity vs. Complexity in time series forecasting: a comparative study of iTransformer variants Open
According to recent time series forecasting research, simpler models frequently perform better than their more complex counterparts, particularly over longer time horizons. By comparing two improved versions of the iTransformer—MiTransform…
View article: Dynamic Aggregation and Augmentation for Low-Resource Machine Translation Using Federated Fine-Tuning of Pretrained Transformer Models
Dynamic Aggregation and Augmentation for Low-Resource Machine Translation Using Federated Fine-Tuning of Pretrained Transformer Models Open
Machine Translation (MT) for low-resource languages, such as Twi, remains a persistent challenge in natural language processing (NLP) due to the scarcity of extensive parallel datasets. Due to their heavy reliance on high-resource data, tr…
View article: LTSMiTransformer: Learnable Temporal Sparsity and Memory for Efficient Long-Term Time Series Forecasting
LTSMiTransformer: Learnable Temporal Sparsity and Memory for Efficient Long-Term Time Series Forecasting Open
Long-term multivariate time series forecasting is critical in domains like finance, climate science, and infrastructure planning, but it faces challenges like high dimensionality, computational inefficiency, and long-range dependency captu…
View article: Dynamic Aggregation and Augmentation for Low-Resource Machine Translation using Federated Fine-tuning of Pretrained Transformer Models
Dynamic Aggregation and Augmentation for Low-Resource Machine Translation using Federated Fine-tuning of Pretrained Transformer Models Open
Machine Translation (MT) for low-resource languages, such as Twi, remains a persistent challenge in Natural Language Processing (NLP) due to the scarcity of extensive parallel datasets. Due to their heavy reliance on high-resource data, tr…
View article: Recent Advances in the Wearable Devices for Monitoring and Management of Heart Failure
Recent Advances in the Wearable Devices for Monitoring and Management of Heart Failure Open
Heart failure (HF) is an acute and degenerative condition with high morbidity and mortality rates. Early diagnosis and treatment of HF can significantly enhance patient outcomes through admission and readmission reduction and improve quali…
View article: Wearable Devices for Monitoring and Management of Heart Failure (Preprint)
Wearable Devices for Monitoring and Management of Heart Failure (Preprint) Open
BACKGROUND Heart failure (HF) represents a significant global health challenge, affecting millions and leading to substantial morbidity and mortality. Wearable devices equipped with sensors and wireless connectivity offers a revolutionary…
View article: Non-Invasive Heart Failure Evaluation Using Machine Learning Algorithms
Non-Invasive Heart Failure Evaluation Using Machine Learning Algorithms Open
Heart failure is a prevalent cardiovascular condition with significant health implications, necessitating effective diagnostic strategies for timely intervention. This study explores the potential of continuous monitoring of non-invasive s…
View article: Non‐Invasive Heart Failure Evaluation with Wearable Signals and Machine Learning Algorithms
Non‐Invasive Heart Failure Evaluation with Wearable Signals and Machine Learning Algorithms Open
Heart failure is a prevalent cardiovascular condition with significant health implications, necessitating effective diagnostic strategies for timely intervention. This study explores the potential of continuous monitoring of non-invasive s…
View article: Wearable Devices for Monitoring and Management of Heart Failure: Systematic Literature Review (Preprint)
Wearable Devices for Monitoring and Management of Heart Failure: Systematic Literature Review (Preprint) Open
BACKGROUND Wearable devices, incorporating sensors, data processing, and wireless connectivity, present transformative tools for comprehensive heart failure care. These devices facilitate continuous monitoring, enabling early decompensati…