6 papers
OSIL: Learning Offline Safe Imitation Policies with Safety Inferred from Non-preferred Trajectories
Returaj Burnwal, Nirav Pravinbhai Bhatt, Balaraman Ravindran
This work addresses the problem of offline safe imitation learning (IL), where the goal is to learn safe and reward-maximizing policies from demonstrations that do not have per-tim…
BiCA: Effective Biomedical Dense Retrieval with Citation-Aware Hard Negatives
Aarush Sinha, Pavan Kumar S, Roshan Balaji +1
Hard negatives are essential for training effective retrieval models. Hard-negative mining typically relies on ranking documents using cross-encoders or static embedding models bas…
SafeMIL: Learning Offline Safe Imitation Policy from Non-Preferred Trajectories
Returaj Burnwal, Nirav Pravinbhai Bhatt, Balaraman Ravindran
In this work, we study the problem of offline safe imitation learning (IL). In many real-world settings, online interactions can be risky, and accurately specifying the reward and…
Learning from Observation: A Survey of Recent Advances
Returaj Burnwal, Hriday Mehta, Nirav Pravinbhai Bhatt +1
Imitation Learning (IL) algorithms offer an efficient way to train an agent by mimicking an expert's behavior without requiring a reward function. IL algorithms often necessitate a…
Functional Groups are All you Need for Chemically Interpretable Molecular Property Prediction
Roshan Balaji, Joe Bobby, Nirav Pravinbhai Bhatt
Molecular property prediction using deep learning (DL) models has accelerated drug and materials discovery, but the resulting DL models often lack interpretability, hindering their…
NovoMolGen: Rethinking Molecular Language Model Pretraining
Kamran Chitsaz, Roshan Balaji, Quentin Fournier +2
Designing de-novo molecules with desired property profiles requires efficient exploration of the vast chemical space ranging from to possible synthesizable cand…