Nagalapatti, Lokesh

11 publications

ICLR 2025 From Search to Sampling: Generative Models for Robust Algorithmic Recourse Prateek Garg, Lokesh Nagalapatti, Sunita Sarawagi

TMLR 2025 Leveraging a Simulator for Learning Causal Representations from Post-Treatment Covariates for CATE Lokesh Nagalapatti, Pranava Singhal, Avishek Ghosh, Sunita Sarawagi

ICLR 2025 Robust Root Cause Diagnosis Using In-Distribution Interventions Lokesh Nagalapatti, Ashutosh Srivastava, Sunita Sarawagi, Amit Sharma

AAAI 2025 Tab-Shapley: Identifying Top-K Tabular Data Quality Insights Manisha Padala, Lokesh Nagalapatti, Atharv Tyagi, Ramasuri Narayanam, Shiv Kumar Saini

AAAI 2024 Continuous Treatment Effect Estimation Using Gradient Interpolation and Kernel Smoothing Lokesh Nagalapatti, Akshay Iyer, Abir De, Sunita Sarawagi

WACV 2024 Gradient Coreset for Federated Learning Durga Sivasubramanian, Lokesh Nagalapatti, Rishabh Iyer, Ganesh Ramakrishnan

NeurIPSW 2024 Leveraging a Simulator for Learning Causal Representations for CATE from Post-Treatment Covariates Lokesh Nagalapatti, Pranava Singhal, Avishek Ghosh, Sunita Sarawagi

ICML 2024 PairNet: Training with Observed Pairs to Estimate Individual Treatment Effect Lokesh Nagalapatti, Pranava Singhal, Avishek Ghosh, Sunita Sarawagi

AAAI 2022 Is Your Data Relevant?: Dynamic Selection of Relevant Data for Federated Learning Lokesh Nagalapatti, Ruhi Sharma Mittal, Ramasuri Narayanam

AAAI 2021 Game of Gradients: Mitigating Irrelevant Clients in Federated Learning Lokesh Nagalapatti, Ramasuri Narayanam

AAAI 2019 Outlier Aware Network Embedding for Attributed Networks Sambaran Bandyopadhyay, Lokesh Nagalapatti, M. Narasimha Murty