Shiv Shankar - RankMe

49 papers A* 9A 5Journal 21Unranked 14

Year	Rank	Type	Title / Venue / Authors
2026	—	`conf`	Energy Matching based Preference Learning for Diffusion Language Models. EACL (Student Research Workshop) Shiv Shankar
2026	—	`conf`	Pseudo-Likelihood Training for Reasoning Diffusion Language Models. EACL (Volume 1: Long Papers) Shiv Shankar
2025	J	`jnl`	Audio-Visual Speech Separation via Bottleneck Iterative Network. CoRR Sidong Zhang, Shiv Shankar, Trang Nguyen, Andrea Fanelli, Madalina Fiterau
2025	—	`conf`	Augmenting Randomized Controlled Trials with Foundation Models as Synthetic Units. BCB Shiv Shankar, Madalina Fiterau
2025	—	`conf`	Combining A/A Data and LLMs for Improved Content Evaluation. WWW (Companion Volume) Shiv Shankar, Ritwik Sinha, Madalina Fiterau
2025	—	`conf`	Controllable Flow-based Hybrid Space Protein Generation. BCB Shiv Shankar
2025	A	`conf`	Experimentation under Treatment Dependent Network Interference. UAI Shiv Shankar, Ritwik Sinha, Madalina Fiterau
2025	J	`jnl`	Learning Straight Flows by Learning Curved Interpolants. CoRR Shiv Shankar, Tomas Geffner
2025	—	`conf`	Using Diffusion Models as Cell Fate Reprogramming Planners. BCB Companion Shiv Shankar
2025	—	`conf`	Using Diffusion Planner for Cell Fate Reprogramming. BCB Shiv Shankar
2024	A	`conf`	A/B testing under Interference with Partial Network Information. AISTATS Shiv Shankar, Ritwik Sinha, Yash Chandak, Saayan Mitra, Madalina Fiterau
2024	J	`jnl`	A/B testing under Interference with Partial Network Information. CoRR Shiv Shankar, Ritwik Sinha, Yash Chandak, Saayan Mitra, Madalina Fiterau
2024	A*	`conf`	Adaptive Instrument Design for Indirect Experiments. ICLR Yash Chandak, Shiv Shankar, Vasilis Syrgkanis, Emma Brunskill
2024	—	`conf`	Estimating Counterfactual Distributions under Interference. ML4H@NeurIPS Shiv Shankar, Ritwik Sinha, Madalina Fiterau
2024	A*	`conf`	On Online Experimentation without Device Identifiers. ICML Shiv Shankar, Ritwik Sinha, Madalina Fiterau
2023	J	`jnl`	Adaptive Instrument Design for Indirect Experiments. CoRR Yash Chandak, Shiv Shankar, Vasilis Syrgkanis, Emma Brunskill
2023	A	`conf`	Direct Inference of Effect of Treatment (DIET) for a Cookieless World. AISTATS Shiv Shankar, Ritwik Sinha, Saayan Mitra, Moumita Sinha, Madalina Fiterau
2023	A	`conf`	Implicit Training of Inference Network Models for Structured Prediction. UAI Shiv Shankar
2023	J	`jnl`	Off-Policy Evaluation for Action-Dependent Non-Stationary Environments. CoRR Yash Chandak, Shiv Shankar, Nathaniel D. Bastian, Bruno Castro da Silva, Emma Brunskill, Philip S. Thomas
2023	J	`jnl`	Optimization using Parallel Gradient Evaluations on Multiple Parameters. CoRR Yash Chandak, Shiv Shankar, Venkata Gandikota, Philip S. Thomas, Arya Mazumdar
2023	A	`conf`	Privacy Aware Experiments without Cookies. WSDM Shiv Shankar, Ritwik Sinha, Saayan Mitra, Viswanathan (Vishy) Swaminathan, Sridhar Mahadevan, Moumita Sinha
2022	J	`jnl`	Implicit Training of Energy Model for Structure Prediction. CoRR Shiv Shankar, Vihari Piratla
2022	—	`conf`	Multimodal fusion via cortical network inspired losses. ACL (1) Shiv Shankar
2022	A*	`conf`	Off-Policy Evaluation for Action-Dependent Non-stationary Environments. NeurIPS Yash Chandak, Shiv Shankar, Nathaniel D. Bastian, Bruno C. da Silva, Emma Brunskill, Philip S. Thomas
2022	J	`jnl`	Privacy Aware Experiments without Cookies. CoRR Shiv Shankar, Ritwik Sinha, Saayan Mitra, Moumita Sinha, Viswanathan Swaminathan, Sridhar Mahadevan
2022	J	`jnl`	Progressive Fusion for Multimodal Integration. CoRR Shiv Shankar, Laure Thompson, Madalina Fiterau
2021	J	`jnl`	Adversarial Stein Training for Graph Energy Models. CoRR Shiv Shankar
2021	J	`jnl`	Bosonic Random Walk Networks for Graph Learning. CoRR Shiv Shankar, Don Towsley
2021	—	`conf`	Bosonic Random Walk Neural Networks for Graph Learning. COMPLEX NETWORKS Shiv Shankar, Don Towsley
2021	A*	`conf`	High-Confidence Off-Policy (or Counterfactual) Variance Estimation. AAAI Yash Chandak, Shiv Shankar, Philip S. Thomas
2021	J	`jnl`	High-Confidence Off-Policy (or Counterfactual) Variance Estimation. CoRR Yash Chandak, Shiv Shankar, Philip S. Thomas
2021	J	`jnl`	Neural Dependency Coding inspired Multimodal Fusion. CoRR Shiv Shankar
2021	—	`conf`	Sibling Regression for Generalized Linear Models. ECML/PKDD (2) Shiv Shankar, Daniel Sheldon
2021	J	`jnl`	Sibling Regression for Generalized Linear Models. CoRR Shiv Shankar, Daniel Sheldon
2021	J	`jnl`	Three-quarter Sibling Regression for Denoising Observational Data. CoRR Shiv Shankar, Daniel Sheldon, Tao Sun, John Pickering, Thomas G. Dietterich
2020	A*	`conf`	Differential Equation Units: Learning Functional Forms of Activation Functions from Data. AAAI MohamadAli Torkamani, Shiv Shankar, Amirmohammad Rooshenas, Phillip Wallis
2020	A*	`conf`	Optimizing for the Future in Non-Stationary MDPs. ICML Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip S. Thomas
2020	J	`jnl`	Optimizing for the Future in Non-Stationary MDPs. CoRR Yash Chandak, Georgios Theocharous, Shiv Shankar, Martha White, Sridhar Mahadevan, Philip S. Thomas
2020	—	`conf`	Rethinking Consumer Email: The Research Process for Yahoo Mail 6. CHI Extended Abstracts Frank Bentley, Josh Jacobson, Charlotte Sperling, Shiv Shankar, Chris Royer, Ian McCarthy
2020	J	`jnl`	Untapped Potential of Data Augmentation: A Domain Generalization Viewpoint. CoRR Vihari Piratla, Shiv Shankar
2019	J	`jnl`	Differential Equation Units: Learning Functional Forms of Activation Functions from Data. CoRR MohamadAli Torkamani, Shiv Shankar, Amirmohammad Rooshenas, Phillip Wallis
2019	J	`jnl`	Learning Compact Neural Networks Using Ordinary Differential Equations as Activation Functions. CoRR MohamadAli Torkamani, Phillip Wallis, Shiv Shankar, Amirmohammad Rooshenas
2019	—	`conf`	Posterior Attention Models for Sequence to Sequence Learning. ICLR (Poster) Shiv Shankar, Sunita Sarawagi
2019	A*	`conf`	Three-quarter Sibling Regression for Denoising Observational Data. IJCAI Shiv Shankar, Daniel Sheldon, Tao Sun, John Pickering, Thomas G. Dietterich
2018	—	`conf`	Generalizing Across Domains via Cross-Gradient Training. ICLR (Poster) Shiv Shankar, Vihari Piratla, Soumen Chakrabarti, Siddhartha Chaudhuri, Preethi Jyothi, Sunita Sarawagi
2018	J	`jnl`	Generalizing Across Domains via Cross-Gradient Training. CoRR Shiv Shankar, Vihari Piratla, Soumen Chakrabarti, Siddhartha Chaudhuri, Preethi Jyothi, Sunita Sarawagi
2018	A*	`conf`	Labeled Memory Networks for Online Model Adaptation. AAAI Shiv Shankar, Sunita Sarawagi
2018	A*	`conf`	Surprisingly Easy Hard-Attention for Sequence to Sequence Learning. EMNLP Shiv Shankar, Siddhant Garg, Sunita Sarawagi
2017	J	`jnl`	Label Organized Memory Augmented Neural Network. CoRR Shiv Shankar, Sunita Sarawagi