Comparison of Deep Reinforcement Learning Policies to Formal Methods for Moving Obstacle Avoidance. - Arpit Garg; Hao-Tien Lewis Chiang; Satomi Sugaya; Aleksandra Faust; Lydia Tapia (IROS, 2019)

Defensive Escort Teams via Multi-Agent Deep Reinforcement Learning. - Arpit Garg; Yazied A. Hasan; Adam Yañez; Lydia Tapia (CoRR, 2019)

Defensive Escort Teams for Navigation in Crowds via Multi-Agent Deep Reinforcement Learning. - Yazied A. Hasan; Arpit Garg; Satomi Sugaya; Lydia Tapia (IEEE Robotics Autom. Lett., 2020)

PeR-ViS: Person Retrieval in Video Surveillance using Semantic Description. - Parshwa Shah; Arpit Garg; Vandit Gajjar (WACV (Workshops), 2021)

Instance-Dependent Noisy Label Learning via Graphical Modelling. - Arpit Garg; Cuong Nguyen 006; Rafael Felix; Thanh-Toan Do; Gustavo Carneiro 001 (WACV, 2023)

PASS: Peer-Agreement based Sample Selection for training with Noisy Labels. - Arpit Garg; Cuong Nguyen 006; Rafael Felix; Thanh-Toan Do; Gustavo Carneiro 001 (CoRR, 2023)

Noisy-label Learning with Sample Selection based on Noise Rate Estimate. - Arpit Garg; Cuong Nguyen 006; Rafael Felix; Thanh-Toan Do; Gustavo Carneiro 001 (CoRR, 2023)

Instance-Dependent Noisy-Label Learning with Graphical Model Based Noise-Rate Estimation. - Arpit Garg; Cuong Nguyen 006; Rafael Felix; Thanh-Toan Do; Gustavo Carneiro 001 (ECCV (4), 2024)

AEON: Adaptive Estimation of Instance-Dependent In-Distribution and Out-of-Distribution Label Noise for Robust Learning. - Arpit Garg; Cuong Nguyen 006; Rafael Felix; Yuyuan Liu; Thanh-Toan Do; Gustavo Carneiro 001 (CoRR, 2025)