Data Driven

Data-driven approaches are revolutionizing scientific research and engineering by leveraging vast datasets to build predictive models and automate complex tasks. Current research focuses on developing and refining algorithms like neural networks (including transformers and graph neural networks), Gaussian processes, and ADMM for diverse applications, ranging from autonomous systems and financial forecasting to scientific discovery and healthcare. This shift towards data-centric methodologies promises to accelerate scientific progress and improve the efficiency and effectiveness of various technological systems, particularly in areas where traditional modeling approaches are limited by complexity or data scarcity.

Papers

July 18, 2024

Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning
Frederik Hoppe, Claudio Mayrink Verdun, Hannah Laus, Felix Krahmer, Holger Rauhut
High Dimensional Uncertainty Quantification Data Driven Sparse Regression

July 15, 2024

Data-Guided Physics-Informed Neural Networks for Solving Inverse Problems in Partial Differential Equations
Wei Zhou, Y. F. Xu
Neural Network Loss Function Physic Informed Neural Network Data Driven Inverse Problem Partial Differential Equation Physic Informed Loss Euler Bernoulli Beam

July 10, 2024

Data-driven Bayesian State Estimation with Compressed Measurement of Model-free Process using Semi-supervised Learning
Anubhab Ghosh, Yonina C. Eldar, Saikat Chatterjee
Semi Supervised Learning Data Driven State Estimation Model Free Pairwise Learning Compressed Measurement State Estimation Problem

July 8, 2024

July 4, 2024

Text2TimeSeries: Enhancing Financial Forecasting through Time Series Prediction Updates with Event-Driven Insights from Large Language Models
Litton Jose Kurisinkel, Pruthwik Mishra, Yue Zhang
Data Driven Time Series Prediction Sentiment Analysis Task Real World Time Series Time Series Model Financial Forecasting Continuous Prediction

July 3, 2024

Learning deformable linear object dynamics from a single trajectory
Shamil Mamedov, A. René Geist, Ruan Viljoen, Sebastian Trimpe, Jan Swevers
Data Driven Neural ODE Robotic Arm Deformable Linear Object Efficient Model

July 1, 2024

FairLay-ML: Intuitive Debugging of Fairness in Data-Driven Social-Critical Software
Normen Yu, Luciana Carreon, Gang Tan, Saeid Tizpaz-Niari
Procedural Fairness Data Driven Code Debugging Counterfactual Fairness Software Developer Counterfactual Situation Testing

June 30, 2024

June 27, 2024

Data-Driven Prediction and Uncertainty Quantification of PWR Crud-Induced Power Shift Using Convolutional Neural Networks
Aidan Furlong, Farah Alsafadi, Scott Palmtag, Andrew Godfrey, Xu Wu
Convolutional Neural Network Uncertainty Quantification Data Driven Model Prediction Nuclear Reactor Prototypical Calibration

June 26, 2024

Long-Term Prediction Accuracy Improvement of Data-Driven Medium-Range Global Weather Forecast
Yifan Hu, Fukang Yin, Weimin Zhang, Kaijun Ren, Junqiang Song, Kefeng Deng, Di Zhang
Data Driven Long Term Prediction Medium Range Shallow Water Equation

June 22, 2024

Privacy Implications of Explainable AI in Data-Driven Systems
Fatima Ezzeddine
Explainable AI High Explainability Data Driven Counterfactual Explanation XAI Method XAI Explanation

June 20, 2024

June 19, 2024

June 13, 2024

DiffPoGAN: Diffusion Policies with Generative Adversarial Networks for Offline Reinforcement Learning
Xuemin Hu, Shen Li, Yingfen Xu, Bo Tang, Long Chen
Generative Adversarial Network Offline Reinforcement Learning Data Driven Diffusion Policy Policy Generation

June 10, 2024

Data Driven

Papers

Non-Asymptotic Uncertainty Quantification in High-Dimensional Learning

Data-Guided Physics-Informed Neural Networks for Solving Inverse Problems in Partial Differential Equations

Data-driven Bayesian State Estimation with Compressed Measurement of Model-free Process using Semi-supervised Learning

Limits and Powers of Koopman Learning

Submodular video object proposal selection for semantic object segmentation

Text2TimeSeries: Enhancing Financial Forecasting through Time Series Prediction Updates with Event-Driven Insights from Large Language Models

Learning deformable linear object dynamics from a single trajectory

FairLay-ML: Intuitive Debugging of Fairness in Data-Driven Social-Critical Software

MUSE-Net: Missingness-aware mUlti-branching Self-attention Encoder for Irregular Longitudinal Electronic Health Records

BADM: Batch ADMM for Deep Learning

Data-Driven Prediction and Uncertainty Quantification of PWR Crud-Induced Power Shift Using Convolutional Neural Networks

Long-Term Prediction Accuracy Improvement of Data-Driven Medium-Range Global Weather Forecast

Privacy Implications of Explainable AI in Data-Driven Systems

Toward data-driven research: preliminary study to predict surface roughness in material extrusion using previously published data with Machine Learning

A Data-Driven Guided Decoding Mechanism for Diagnostic Captioning

You can't handle the (dirty) truth: Data-centric insights improve pseudo-labeling

Leveraging Large Language Models for Patient Engagement: The Power of Conversational AI in Digital Health

DiffPoGAN: Diffusion Policies with Generative Adversarial Networks for Offline Reinforcement Learning

Random Features Approximation for Control-Affine Systems

Predicting Heart Activity from Speech using Data-driven and Knowledge-based features