Label Organized Memory Augmented Neural Network. - Shiv Shankar; Sunita Sarawagi (CoRR, 2017)

Labeled Memory Networks for Online Model Adaptation. - Shiv Shankar; Sunita Sarawagi (AAAI, 2018)

Surprisingly Easy Hard-Attention for Sequence to Sequence Learning. - Shiv Shankar; Siddhant Garg; Sunita Sarawagi (EMNLP, 2018)

Generalizing Across Domains via Cross-Gradient Training. - Shiv Shankar; Vihari Piratla; Soumen Chakrabarti; Siddhartha Chaudhuri; Preethi Jyothi; Sunita Sarawagi (ICLR (Poster), 2018)

Posterior Attention Models for Sequence to Sequence Learning. - Shiv Shankar; Sunita Sarawagi (ICLR (Poster), 2019)

Three-quarter Sibling Regression for Denoising Observational Data. - Shiv Shankar; Daniel Sheldon; Tao Sun 008; John Pickering; Thomas G. Dietterich (IJCAI, 2019)

Learning Compact Neural Networks Using Ordinary Differential Equations as Activation Functions. - MohamadAli Torkamani; Phillip Wallis; Shiv Shankar; Amirmohammad Rooshenas (CoRR, 2019)

Differential Equation Units: Learning Functional Forms of Activation Functions from Data. - MohamadAli Torkamani; Shiv Shankar; Amirmohammad Rooshenas; Phillip Wallis (AAAI, 2020)

Rethinking Consumer Email: The Research Process for Yahoo Mail 6. - Frank Bentley; Josh Jacobson; Charlotte Sperling; Shiv Shankar; Chris Royer; Ian McCarthy (CHI Extended Abstracts, 2020)

Optimizing for the Future in Non-Stationary MDPs. - Yash Chandak; Georgios Theocharous; Shiv Shankar; Martha White; Sridhar Mahadevan; Philip S. Thomas (ICML, 2020)

Untapped Potential of Data Augmentation: A Domain Generalization Viewpoint. - Vihari Piratla; Shiv Shankar (CoRR, 2020)

High-Confidence Off-Policy (or Counterfactual) Variance Estimation. - Yash Chandak; Shiv Shankar; Philip S. Thomas (AAAI, 2021)

Bosonic Random Walk Neural Networks for Graph Learning. - Shiv Shankar; Don Towsley (COMPLEX NETWORKS, 2021)

Sibling Regression for Generalized Linear Models. - Shiv Shankar; Daniel Sheldon (ECML/PKDD (2), 2021)

Bosonic Random Walk Networks for Graph Learning. - Shiv Shankar; Don Towsley (CoRR, 2021)

Adversarial Stein Training for Graph Energy Models. - Shiv Shankar (CoRR, 2021)

Neural Dependency Coding inspired Multimodal Fusion. - Shiv Shankar (CoRR, 2021)

Multimodal fusion via cortical network inspired losses. - Shiv Shankar (ACL (1), 2022)

Off-Policy Evaluation for Action-Dependent Non-stationary Environments. - Yash Chandak; Shiv Shankar; Nathaniel D. Bastian; Bruno C. da Silva 001; Emma Brunskill; Philip S. Thomas (NeurIPS, 2022)

Progressive Fusion for Multimodal Integration. - Shiv Shankar; Laure Thompson; Madalina Fiterau (CoRR, 2022)

Implicit Training of Energy Model for Structure Prediction. - Shiv Shankar; Vihari Piratla (CoRR, 2022)

Direct Inference of Effect of Treatment (DIET) for a Cookieless World. - Shiv Shankar; Ritwik Sinha; Saayan Mitra; Moumita Sinha; Madalina Fiterau (AISTATS, 2023)

Implicit Training of Inference Network Models for Structured Prediction. - Shiv Shankar (UAI, 2023)

Privacy Aware Experiments without Cookies. - Shiv Shankar; Ritwik Sinha; Saayan Mitra; Viswanathan (Vishy) Swaminathan; Sridhar Mahadevan; Moumita Sinha (WSDM, 2023)

Optimization using Parallel Gradient Evaluations on Multiple Parameters. - Yash Chandak; Shiv Shankar; Venkata Gandikota; Philip S. Thomas; Arya Mazumdar (CoRR, 2023)

A/B testing under Interference with Partial Network Information. - Shiv Shankar; Ritwik Sinha; Yash Chandak; Saayan Mitra; Madalina Fiterau (AISTATS, 2024)

Adaptive Instrument Design for Indirect Experiments. - Yash Chandak; Shiv Shankar; Vasilis Syrgkanis; Emma Brunskill (ICLR, 2024)

On Online Experimentation without Device Identifiers. - Shiv Shankar; Ritwik Sinha; Madalina Fiterau (ICML, 2024)

Estimating Counterfactual Distributions under Interference. - Shiv Shankar; Ritwik Sinha; Madalina Fiterau (ML4H@NeurIPS, 2024)

Experimentation under Treatment Dependent Network Interference. - Shiv Shankar; Ritwik Sinha; Madalina Fiterau (UAI, 2025)

Combining A/A Data and LLMs for Improved Content Evaluation. - Shiv Shankar; Ritwik Sinha; Madalina Fiterau (WWW (Companion Volume), 2025)

Learning Straight Flows by Learning Curved Interpolants. - Shiv Shankar; Tomas Geffner (CoRR, 2025)

Audio-Visual Speech Separation via Bottleneck Iterative Network. - Sidong Zhang; Shiv Shankar; Trang Nguyen; Andrea Fanelli; Madalina Fiterau (CoRR, 2025)