68 citations · 138 across the 22 of their papers we have counts for
4 papers · 1 filter
LaGR-SEQ: Language-Guided Reinforcement Learning with Sample-Efficient Querying
Thommen George Karimpanal, Laknath Buddhika Semage, Santu Rana +4
Large language models (LLMs) have recently demonstrated their impressive ability to provide context-aware responses via text. This ability could potentially be used to predict plau…
Predictive Modeling through Hyper-Bayesian Optimization
Manisha Senadeera, Santu Rana, Sunil Gupta +1
Model selection is an integral problem of model based optimization techniques such as Bayesian optimization (BO). Current approaches often treat model selection as an estimation pr…
BO-Muse: A human expert and AI teaming framework for accelerated experimental design
Sunil Gupta, Alistair Shilton, Arun Kumar A +7
In this paper we introduce BO-Muse, a new approach to human-AI teaming for the optimization of expensive black-box functions. Inspired by the intrinsic difficulty of extracting exp…
Gradient Descent in Neural Networks as Sequential Learning in RKBS
Alistair Shilton, Sunil Gupta, Santu Rana +1
The study of Neural Tangent Kernels (NTKs) has provided much needed insight into convergence and generalization properties of neural networks in the over-parametrized (wide) limit…