Nikhil Mehta
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Stochastic blockmodels meet graph neural networks
N Mehta, L Carin, P Rai
International Conference on Machine Learning (ICML), 2019
Continual Learning using a Bayesian Nonparametric Dictionary of Weight Factors
N Mehta, K Liang, VK Verma, L Carin
International Conference on Artificial Intelligence and Statistics, 100-108, 2021
Counterfactual representation learning with balancing weights
S Assaad, S Zeng, C Tao, S Datta, N Mehta, R Henao, F Li, LC Duke
International Conference on Artificial Intelligence and Statistics, 1972-1980, 2021
Survival cluster analysis
P Chapfuwa, C Li, N Mehta, L Carin, R Henao
ACM Conference on Health, Inference, and Learning (CHIL), 2020
WAFFLe: Weight Anonymized Factorization for Federated Learning
W Hao, N Mehta, KJ Liang, P Cheng, M El-Khamy, L Carin
arXiv preprint arXiv:2008.05687, 2020
Graph Representation Learning via Ladder Gamma Variational Autoencoders
A Sarkar, N Mehta, P Rai
Association for the Advancement of Artificial Intelligence (AAAI), 2020
Deep topic models for multi-label learning
R Panda, A Pensia, N Mehta, M Zhou, P Rai
The 22nd International Conference on AISTATS, 2849-2857, 2019
Meta-learned attribute self-gating for continual generalized zero-shot learning
VK Verma, K Liang, N Mehta, L Carin
arXiv preprint arXiv:2102.11856, 2021
Efficient Feature Transformations for Discriminative and Generative Continual Learning
VK Verma, KJ Liang, N Mehta, P Rai, L Carin
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
Estimation and Sampling of Unnormalized Statistical Models with Stein Score Matching
J Liu, N Mehta, C Tao, L Carin
ICML Workshop on Stein's Method for Machine Learning and Statistics, 2019
Robust and Fast 3D Scan Alignment using Mutual Information
N Mehta, JR McBride, G Pandey
2018 IEEE International Conference on Robotics and Automation (ICRA), 3413-3420, 2018
Learning interpretable hierarchical node representations via Ladder Gamma VAE
A Sarkar, N Mehta, P Rai
NeurIPS 2019 Workshop on Graph Representation Learning, 0
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