22 citations · 32 across the 6 of their papers we have counts for
6 papers
Open RL Benchmark: Comprehensive Tracked Experiments for Reinforcement Learning
Shengyi Huang, Quentin Gallouédec, Florian Felten +30
In many Reinforcement Learning (RL) papers, learning curves are useful indicators to measure the effectiveness of RL algorithms. However, the complete raw data of the learning curv…
marl-jax: Multi-Agent Reinforcement Leaning Framework
Kinal Mehta, Anuj Mahajan, Pawan Kumar
Recent advances in Reinforcement Learning (RL) have led to many exciting applications. These advancements have been driven by improvements in both algorithms and engineering, which…
Effects of Spectral Normalization in Multi-agent Reinforcement Learning
Kinal Mehta, Anuj Mahajan, Pawan Kumar
A reliable critic is central to on-policy actor-critic learning. But it becomes challenging to learn a reliable critic in a multi-agent sparse reward scenario due to two factors: 1…
ReF -- Rotation Equivariant Features for Local Feature Matching
Abhishek Peri, Kinal Mehta, Avneesh Mishra +3
Sparse local feature matching is pivotal for many computer vision and robotics tasks. To improve their invariance to challenging appearance conditions and viewing angles, and hence…
RoRD: Rotation-Robust Descriptors and Orthographic Views for Local Feature Matching
Udit Singh Parihar, Aniket Gujarathi, Kinal Mehta +4
The use of local detectors and descriptors in typical computer vision pipelines work well until variations in viewpoint and appearance change become extreme. Past research in this…
W-Net: Reinforced U-Net for Density Map Estimation
Varun Kannadi Valloli, Kinal Mehta
Crowd management is of paramount importance when it comes to preventing stampedes and saving lives, especially in a countries like China and India where the combined population is…