papers

Publications (5)

cs.LG2026

B-DENSE: Branching For Dense Ensemble Network Supervision Efficiency

Cherish Puniani, Tushar Kumar, Arnav Bendre +2

Inspired by non-equilibrium thermodynamics, diffusion models have achieved state-of-the-art performance in generative modeling. However, their iterative sampling nature results in…

cs.CV2020

Grounding-Tracking-Integration

Zhengyuan Yang, Tushar Kumar, Tianlang Chen +2

In this paper, we study Tracking by Language that localizes the target box sequence in a video based on a language query. We propose a framework called GTI that decomposes the prob…

cs.RO2021

Decentralized Control of Quadrotor Swarms with End-to-end Deep Reinforcement Learning

Sumeet Batra, Zhehui Huang, Aleksei Petrenko +3

We demonstrate the possibility of learning drone swarm controllers that are zero-shot transferable to real quadrotors via large-scale multi-agent end-to-end reinforcement learning.…

cs.LG2020

Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning

Aleksei Petrenko, Zhehui Huang, Tushar Kumar +2

Increasing the scale of reinforcement learning experiments has allowed researchers to achieve unprecedented results in both training sophisticated agents for video games, and in si…

cs.RO2023

QuadSwarm: A Modular Multi-Quadrotor Simulator for Deep Reinforcement Learning with Direct Thrust Control

Zhehui Huang, Sumeet Batra, Tao Chen +7

Reinforcement learning (RL) has shown promise in creating robust policies for robotics tasks. However, contemporary RL algorithms are data-hungry, often requiring billions of envir…