4 citations · 9 across the 13 of their papers we have counts for
6 papers · 1 filter
Direction-Conditioned Policies for Online Goal-Conditioned Reinforcement Learning
S K Swaminathan, Damiya Gondha, Theyanesh Eswaramoorthy Rajahkrishnan +1
Contrastive Reinforcement Learning (CRL) learns representations that estimate goal reachability, yet its policy remains conditioned on raw goals and therefore does not directly exp…
BackgroundMellow: A Multi-Modal Cohesive Framework for Narrative-Driven Rich Cinematic Soundscape Generation
Ajitesh Jamulkar, Aritra Hazra
Generating immersive, synchronized and cinematic audio for long-form textual narratives remains a significant challenge in multi-modal AI. While current Text-to-Audio (TTA) framewo…
Direction-Conditioned Policies via Compositional Subgoal Scoring for Online Goal-Conditioned Reinforcement Learning
Swaminathan S K, Damiya Gondha, Theyanesh Eswaramoorthy Rajahkrishnan +1
Hamilton-Jacobi-Bellman theory implies that the optimal goal-conditioned action depends on the goal only through the gradient of the goal-reaching distance at the current state, ye…
SPAARS: Safer RL Policy Alignment through Abstract Exploration and Refined Exploitation of Action Space
Swaminathan S K, Aritra Hazra
Offline-to-online reinforcement learning (RL) offers a promising paradigm for robotics by pre-training policies on safe, offline demonstrations and fine-tuning them via online inte…
Towards Adversarial Purification using Denoising AutoEncoders
Dvij Kalaria, Aritra Hazra, Partha Pratim Chakrabarti
With the rapid advancement and increased use of deep learning models in image identification, security becomes a major concern to their deployment in safety-critical systems. Since…
Detecting Adversaries, yet Faltering to Noise? Leveraging Conditional Variational AutoEncoders for Adversary Detection in the Presence of Noisy Images
Dvij Kalaria, Aritra Hazra, Partha Pratim Chakrabarti
With the rapid advancement and increased use of deep learning models in image identification, security becomes a major concern to their deployment in safety-critical systems. Since…