Anish Abhijit Diwan — accepted AI-conference papers

2026

Trust Region Inverse Reinforcement Learning

Anish Abhijit Diwan, Davide Tateo, Christopher Mower, Haitham Bou Ammar, Jan Peters, Oleg Arenz

ICML 2026poster

Inverse reinforcement learning (IRL) is typically formulated as maximizing entropy subject to matching the distribution of expert trajectories. Classical (dual-ascent) IRL guarantees monotonic performance improvement but requires fully solving an RL problem each iteration to compute dual gradients. …

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2025

Noise-conditioned Energy-based Annealed Rewards (NEAR): A Generative Framework for Imitation Learning from Observation

Anish Abhijit Diwan, Julen Urain, Jens Kober, Jan Peters

ICLR 2025poster

This paper introduces a new imitation learning framework based on energy-based generative models capable of learning complex, physics-dependent, robot motion policies through state-only expert motion trajectories. Our algorithm, called Noise-conditioned Energy-based Annealed Rewards (NEAR), construc…

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