IEEE

Data-Driven Motion Planning: A Survey on Deep Neural Networks, Reinforcement Learning, and Large Language Model Approaches

Abstract: Motion planning is a fundamental challenge in robotics, involving the creation of trajectories from start to goal states while meeting constraints like collision avoidance and joint limits.
IEEE

Deep Reinforcement Learning with Graph Neural Networks: An Indepth Analysis of Algorithms and Applications

Abstract: Deep Reinforcement Learning (DRL) enable several areas of artificial intelligence, including perception recognition, expert system, recommender program and game. Also, graph neural networks ...
GitHub

TabM: Advancing Tabular Deep Learning With Parameter-Efficient Ensembling" (ICLR 2025)

This is the official repository of the paper "TabM: Advancing Tabular Deep Learning With Parameter-Efficient Ensembling". It consists of two parts: One dot represents a performance score on one ...
Morning Overview on MSN

Brain scans reveal an internal "dial" that keeps you from getting lost

Human navigation turns out to be less like following a static map and more like tuning a control knob inside the brain. New ...