The Impact Of Large-Scale Language Models On Scientific Discovery: A Preliminary Study Using GPT-4
The Impact Of Large-Scale Language Models On Scientific Discovery: A Preliminary Study Using GPT-4
Large Language Models
Universal Deoxidation Of Semiconductor Substrates Using Machine Learning And Real-time Feedback Control
Universal Deoxidation Of Semiconductor Substrates Using Machine Learning And Real-time Feedback Cont ...
Machine Learning
Topological Data Analysis In Smart Manufacturing Processes--A Survey Of Current Technologies
Topological Data Analysis In Smart Manufacturing Processes--A Survey Of Current Technologies
Topological Data Analysis
Review: Image Conversion Of IoT Time Series Data And Various Applications
Review: Image Conversion Of IoT Time Series Data And Various Applications
Internet Of Things
Fast, Inexpensive Machine Learning For Manufacturing Processes Learning Transitions From Physical Models
Fast, Inexpensive Machine Learning For Manufacturing Processes Learning Transitions From Physical Mo ...
Transfer Learning
Maximizing Model Generalization In Manufacturing Through Self-Supervised And Integrated Learning
Maximizing Model Generalization In Manufacturing Through Self-Supervised And Integrated Learning
Federated Learning
Federated Learning-based Integrated Object Detection That Leverages Distributed Data While Protecting Privacy
Federated Learning-based Integrated Object Detection That Leverages Distributed Data While Protectin ...
Federated Learning
Adversarial Domain Adaptation To Address The Problem Of Lack Of Labeled Training Data
Adversarial Domain Adaptation To Address The Problem Of Lack Of Labeled Training Data
Domain Adaption
Time Series Data Clustering With Quantum Computing (annealing Machines)
Time Series Data Clustering With Quantum Computing (annealing Machines)
Time-series
WaveBound, A Regularization Method That Prevents Overlearning In Dynamic Time Series Data And Improves Prediction Accuracy
WaveBound, A Regularization Method That Prevents Overlearning In Dynamic Time Series Data And Improv ...
Time-series
Time-Frequency Consistency (TF-C), The First Realization Of Prior Learning In Time Series With Self-supervised Contrasted Learning
Time-Frequency Consistency (TF-C), The First Realization Of Prior Learning In Time Series With Self- ...
Time-series
Unsteady Transformer
Unsteady Transformer
Time-series
LATM Generates And Executes Extension Tools Using LLM
LATM Generates And Executes Extension Tools Using LLM
Large Language Models
Tree Of Thought: Incorporating System 2 Concepts Into LLM, Even More Powerful Than CoT-based GPT-4
Tree Of Thought: Incorporating System 2 Concepts Into LLM, Even More Powerful Than CoT-based GPT-4
Large Language Models
Predictive Performance SCINet Beyond Transformers
Predictive Performance SCINet Beyond Transformers
Time-series
FiLM Solves The Trade-off Between Noise Removal And Variability Detection In Time Series Forecasting Models.
FiLM Solves The Trade-off Between Noise Removal And Variability Detection In Time Series Forecasting ...
Time-series
Time Series Classification Dynamic Sparse Network DNS That Learns Over A Wide Receptive Field Without Complex Tuning
Time Series Classification Dynamic Sparse Network DNS That Learns Over A Wide Receptive Field Withou ...
Time-series
Time Series Forecasting D3VAE Using Generative Models
Time Series Forecasting D3VAE Using Generative Models
Time-series