IEEE

Reinforcement Learning Autonomous Driving via Reward Function Design in Simulation

Abstract: In this paper, we present a deep-reinforcement learning(RL) approach to autonomous driving in a simulated environment, supported by a carefully crafted reward function. Using Unity's ...
The Manila Times

Chongwei Shi Advances Biostatistical Methods and Computational Biology Through Deep Learning and Statistical Shape Analysis

A deep learning framework combines convolutional and bidirectional recurrent networks to improve protein function prediction from genomic sequences. By automating feature extraction and capturing long ...
IEEE

PINN-Based Seismic Wavefield Simulation With Learnable Multiscale Fourier Feature Mapping and Adaptive Activation Function

Abstract: Seismic wavefield simulation is crucial for acquisition design, inversion, and interpretation in seismic exploration. The essence of seismic wavefield simulation is to solve wave equations.