Data Science & AI Research

research

∙ 01/25/2023

Distributed Control of Partial Differential Equations Using Convolutional Reinforcement Learning

We present a convolutional framework which significantly reduces the com...

Sebastian Peitz, et al. ∙

research

∙ 01/09/2023

Advances in Medical Image Analysis with Vision Transformers: A Comprehensive Review

The remarkable performance of the Transformer architecture in natural la...

Reza Azad, et al. ∙

research

∙ 01/30/2023

Curvature Filtrations for Graph Generative Model Evaluation

Graph generative model evaluation necessitates understanding differences...

Joshua Southern, et al. ∙

research

∙ 01/19/2023

AtMan: Understanding Transformer Predictions Through Memory Efficient Attention Manipulation

Generative transformer models have become increasingly complex, with lar...

Mayukh Deb, et al. ∙

research

∙ 01/19/2023

Forecasting subcritical cylinder wakes with Fourier Neural Operators

We apply Fourier neural operators (FNOs), a state-of-the-art operator le...

Peter I Renn, et al. ∙

research

∙ 01/19/2023

Learning ultrasound plane pose regression: assessing generalized pose coordinates in the fetal brain

In obstetric ultrasound (US) scanning, the learner's ability to mentally...

Chiara Di Vece, et al. ∙

research

∙ 02/02/2023

Double Permutation Equivariance for Knowledge Graph Completion

This work provides a formalization of Knowledge Graphs (KGs) as a new cl...

Jianfei Gao, et al. ∙

research

∙ 01/18/2023

Semi-Supervised Semantic Segmentation via Gentle Teaching Assistant

Semi-Supervised Semantic Segmentation aims at training the segmentation ...

Ying Jin, et al. ∙

research

∙ 01/25/2023

Knowledge-augmented Graph Neural Networks with Concept-aware Attention for Adverse Drug Event Detection

Adverse drug events (ADEs) are an important aspect of drug safety. Vario...

Shaoxiong Ji, et al. ∙

research

∙ 01/12/2023

Asynchronous training of quantum reinforcement learning

The development of quantum machine learning (QML) has received a lot of ...

Samuel Yen-Chi Chen, et al. ∙

research

∙ 01/26/2023

A Benchmark Study by using various Machine Learning Models for Predicting Covid-19 trends

Machine learning and deep learning play vital roles in predicting diseas...

D. Kamelesun, et al. ∙