10 citations · 10 across the 5 of their papers we have counts for
5 papers
On the Transferability of Agricultural Weed Detection Under Cross-Field Distribution Shift
Nikhilesh Prabhakar, Pranuthi Tenali, Wilfredo Abudeye Fernandez +5
Accurate agricultural weed detection in real-world field conditions is essential for precision agriculture, enabling targeted intervention and reducing yield loss. Recent work has…
Neurosymbolic Imitation Learning with Human Guidance: A Privileged Information Approach
Nikhilesh Prabhakar, Varun Balaji, Athresh Karanam +2
Imitation learning is widely used for learning to act in complex environments. While pure neural-based methods handle high dimensional data effectively, they suffer from the requir…
A Unified Framework for Human-Allied Learning of Probabilistic Circuits
Athresh Karanam, Saurabh Mathur, Sahil Sidheekh +1
Probabilistic Circuits (PCs) have emerged as an efficient framework for representing and learning complex probability distributions. Nevertheless, the existing body of research on…
Explaining Deep Tractable Probabilistic Models: The sum-product network case
Athresh Karanam, Saurabh Mathur, Predrag Radivojac +3
We consider the problem of explaining a class of tractable deep probabilistic models, the Sum-Product Networks (SPNs) and present an algorithm ExSPN to generate explanations. To th…
Interventional Sum-Product Networks: Causal Inference with Tractable Probabilistic Models
Matej Zečević, Devendra Singh Dhami, Athresh Karanam +2
While probabilistic models are an important tool for studying causality, doing so suffers from the intractability of inference. As a step towards tractable causal models, we consid…