On the design fundamentals of diffusion models: A survey
Diffusion models are generative models, which gradually add and remove noise to learn the
underlying distribution of training data for data generation. The components of diffusion …
underlying distribution of training data for data generation. The components of diffusion …
Dewave: Discrete encoding of eeg waves for eeg to text translation
The translation of brain dynamics into natural language is pivotal for brain-computer
interfaces (BCIs), a field that has seen substantial growth in recent years. With the swift …
interfaces (BCIs), a field that has seen substantial growth in recent years. With the swift …
A comprehensive survey on generative diffusion models for structured data
In recent years, generative diffusion models have achieved a rapid paradigm shift in deep
generative models by showing groundbreaking performance across various applications …
generative models by showing groundbreaking performance across various applications …
Dewave: Discrete eeg waves encoding for brain dynamics to text translation
The translation of brain dynamics into natural language is pivotal for brain-computer
interfaces (BCIs), a field that has seen substantial growth in recent years. With the swift …
interfaces (BCIs), a field that has seen substantial growth in recent years. With the swift …
A Survey on Generative Diffusion Models for Structured Data
H Koo - arXiv preprint arXiv:2306.04139, 2023 - arxiv.org
In recent years, generative diffusion models have achieved a rapid paradigm shift in deep
generative models by showing groundbreaking performance across various applications …
generative models by showing groundbreaking performance across various applications …
A survey on diffusion models for time series and spatio-temporal data
The study of time series data is crucial for understanding trends and anomalies over time,
enabling predictive insights across various sectors. Spatio-temporal data, on the other hand …
enabling predictive insights across various sectors. Spatio-temporal data, on the other hand …
Synthetic sleep EEG signal generation using latent diffusion models
B Aristimunha, RY de Camargo… - … Generative Models for …, 2023 - openreview.net
Electroencephalography (EEG) is a non-invasive method that allows for recording rich
temporal information and is a valuable tool for diagnosing various neurological and …
temporal information and is a valuable tool for diagnosing various neurological and …
Parameter sharing fault data generation method based on diffusion model under imbalance data
Z Xiao, C Li, T Liu, W Liu, S Mo… - … Science and Technology, 2024 - iopscience.iop.org
Rotating machinery will inevitably fail under long-term heavy load working conditions.
Obtaining enough data to train the deep learning model can enable managers to detect and …
Obtaining enough data to train the deep learning model can enable managers to detect and …
Fingerprinting in EEG Model IP Protection Using Diffusion Model
T Wang, S Zhong - Proceedings of the 2024 International Conference on …, 2024 - dl.acm.org
In the rapidly advancing field of deep learning, a significant yet often overlooked challenge
is the protection of intellectual property (IP) for models based on electroencephalography …
is the protection of intellectual property (IP) for models based on electroencephalography …
A Comprehensive Survey of Hypermedia System for Text-to-Image Conversion Using Generative AI
T Majumdar, S Sahu, R Kumar - The Pioneering Applications of …, 2024 - igi-global.com
The intersection of computer vision and natural language processing (NLP) has witnessed
significant advancements in recent research, particularly in the realm of converting text into …
significant advancements in recent research, particularly in the realm of converting text into …