This repository includes the training and evaluation code for the above paper. python train_script.py --name data_physics --data True --physics True --pretrained_checkpoint DATA_CHECKPOINT ...

This is the official implementation used in the paper Towards Generalizability of Multi-Agent Reinforcement Learning in Graphs with Recurrent Message Passing (arXiv), which has been accepted for ...

Abstract: A dynamic multi-scale spatiotemporal graph recurrent neural network (DMST-GRNN) model has been introduced, which is leveraged to use human motion prediction on a 3D skeleton-based human ...

Abstract: A variety of real-world applications rely on accurate predictions of 3D human motion from their past observations. While existing methods have made notable progress, their predictions over ...

From the Paris ed. of Messrs. de Condorcet & de La Croix, 1787; with the restoration of several passages from the original ed., that of Mietau and Leipsic, 1770. cf. Pref. Press figures in v. 2 ...