Pratik Bhowal — accepted AI-conference papers

2025

ArticuBot: Learning Universal Articulated Object Manipulation Policy via Large Scale Simulation

Yufei Wang, Ziyu Wang, Mino Nakura, Pratik Bhowal, Chia-Liang Kuo, Yi-Ting Chen +2

RSS 2025poster

This paper presents ArticuBot, in which a single learned policy enables a robotics system to open diverse categories of unseen articulated objects in the real world. This task has long been challenging for robotics due to the large variations in the geometry, size, and articulation types of such ob…

Cited by 0 PDF ↗Scholar ↗

2024

Why do Variational Autoencoders Really Promote Disentanglement?

Pratik Bhowal, Achint Soni, Sirisha Rambhatla

ICML 2024poster

Despite not being designed for this purpose, the use of variational autoencoders (VAEs) has proven remarkably effective for disentangled representation learning (DRL). Recent research attributes this success to certain characteristics of the loss function that prevent latent space rotation, or hypot…

Cited by 4 Source ↗PDF ↗code ↗Scholar ↗