Intuitionistic fuzzy ant colony optimization for course sequencing in E-learning. - Siddhant Agarwal; Mukta Goyal; Adarsh Kumar; K. Rajalakshmi 001 (IC3, 2016)

Traffic Sign Classification using Hybrid HOG-SURF Features and Convolutional Neural Networks. - Rishabh Madan; Deepank Agrawal; Shreyas Kowshik; Harsh Maheshwari; Siddhant Agarwal; Debashish Chakravarty (ICPRAM, 2019)

Poisoned classifiers are not only backdoored, they are fundamentally broken. - Mingjie Sun; Siddhant Agarwal; J. Zico Kolter (CoRR, 2020)

Learning to Deceive Knowledge Graph Augmented Models via Targeted Perturbation. - Mrigank Raman; Aaron Chan; Siddhant Agarwal; Peifeng Wang; Hansen Wang; Sungchul Kim; Ryan A. Rossi; Handong Zhao; Nedim Lipka; Xiang Ren 001 (ICLR, 2021)

Deep learning for surrogate modelling of 2D mantle convection. - Siddhant Agarwal; Nicola Tosi; Pan Kessel; Doris Breuer; Grégoire Montavon (CoRR, 2021)

Reinforcement Explanation Learning. - Siddhant Agarwal; Owais Iqbal; Sree Aditya Buridi; Madda Manjusha; Abir Das (CoRR, 2021)

What Do You MEME? Generating Explanations for Visual Semantic Role Labelling in Memes. - Shivam Sharma; Siddhant Agarwal; Tharun Suresh; Preslav Nakov; Md. Shad Akhtar; Tanmoy Chakraborty 002 (AAAI, 2023)

f-Policy Gradients: A General Framework for Goal-Conditioned RL using f-Divergences. - Siddhant Agarwal; Ishan Durugkar; Peter Stone 001; Amy Zhang 001 (NeurIPS, 2023)

MemeMQA: Multimodal Question Answering for Memes via Rationale-Based Inferencing. - Siddhant Agarwal; Shivam Sharma; Preslav Nakov; Tanmoy Chakraborty 002 (ACL (Findings), 2024)

Robot Air Hockey: A Manipulation Testbed for Robot Learning with Reinforcement Learning. - Caleb Chuck; Carl Qi; Michael J. Munje; Shuozhe Li; Max Rudolph; Chang Shi; Siddhant Agarwal; Harshit Sikchi; Abhinav Peri; Sarthak Dayal; Evan Kuo; Kavan Mehta; et al. (CoRR, 2024)

Aero-Nef: Neural Fields for Rapid Aircraft Aerodynamics Simulations. - Giovanni Catalani; Siddhant Agarwal; Xavier Bertrand; Frederic Tost; Michael Bauerheim; Joseph Morlier (CoRR, 2024)

Accelerating the discovery of steady-states of planetary interior dynamics with machine learning. - Siddhant Agarwal; Nicola Tosi; Christian Hüttig; David S. Greenberg; Ali Can Bekar (CoRR, 2024)

Proto Successor Measure: Representing the Space of All Possible Solutions of Reinforcement Learning. - Siddhant Agarwal; Harshit Sikchi; Peter Stone 001; Amy Zhang 001 (CoRR, 2024)

RL Zero: Zero-Shot Language to Behaviors without any Supervision. - Harshit Sikchi; Siddhant Agarwal; Pranaya Jajoo; Samyak Parajuli; Caleb Chuck; Max Rudolph; Peter Stone 001; Amy Zhang 001; Scott Niekum (CoRR, 2024)

Reinforcement Learning Within the Classical Robotics Stack: A Case Study in Robot Soccer. - Adam Labiosa; Zhihan Wang; Siddhant Agarwal; William Cong; Geethika Hemkumar; Abhinav Narayan Harish; Benjamin Hong; Josh Kelle; Chen Li; Yuhao Li; Zisen Shao; Peter Stone 001; et al. (CoRR, 2024)

Null Counterfactual Factor Interactions for Goal-Conditioned Reinforcement Learning. - Caleb Chuck; Fan Feng; Carl Qi; Chang Shi; Siddhant Agarwal; Amy Zhang 001; Scott Niekum (ICLR, 2025)

Physics-based machine learning for mantle convection simulations. - Siddhant Agarwal; Ali Can Bekar; Christian Hüttig; David S. Greenberg; Nicola Tosi (CoRR, 2025)