activity
20172021
most citedOptimizing for the Future in Non-Stationary MDPs

8 citations · 20 across the 9 of their papers we have counts for

collaborators

12 papers

cs.NE20211 cited

Neural Dependency Coding inspired Multimodal Fusion

Shiv Shankar

Information integration from different modalities is an active area of research. Human beings and, in general, biological neural systems are quite adept at using a multitude of sig…

cs.LG2021

Adversarial Stein Training for Graph Energy Models

Shiv Shankar

Learning distributions over graph-structured data is a challenging task with many applications in biology and chemistry. In this work we use an energy-based model (EBM) based on mu…

stat.ME2021

Sibling Regression for Generalized Linear Models

Shiv Shankar, Daniel Sheldon

Field observations form the basis of many scientific studies, especially in ecological and social sciences. Despite efforts to conduct such surveys in a standardized way, observati…

cs.LG20211 cited

High-Confidence Off-Policy (or Counterfactual) Variance Estimation

Yash Chandak, Shiv Shankar, Philip S. Thomas

Many sequential decision-making systems leverage data collected using prior policies to propose a new policy. For critical applications, it is important that high-confidence guaran…

cs.LG20201 cited

Bosonic Random Walk Networks for Graph Learning

Shiv Shankar, Don Towsley

The development of Graph Neural Networks (GNNs) has led to great progress in machine learning on graph-structured data. These networks operate via diffusing information across the…

stat.ME2020

Three-quarter Sibling Regression for Denoising Observational Data

Shiv Shankar, Daniel Sheldon, Tao Sun +2

Many ecological studies and conservation policies are based on field observations of species, which can be affected by systematic variability introduced by the observation process.…