I am an AI researcher working broadly in the domains of probabilistic generative models and meta-learning. I also explore applications of deep learning to novel problems that can impact society for the better. Previously, I completed by undergraduate studies majoring in Computer Science and Engineering from IIT Ropar, where I was fortunate to be a part of the LSAIML team headed by Dr. Narayanan C. K.
I am passionate about building robust and efficient systems that can reason probabilistically and make interpretable decisions. I enjoy connecting dots and innovating ideas that span multiple disciplines. I have a strong academic background in engineering and machine learning. If you would like to collaborate, please feel free to reach out through email .
|May 16, 2022||
Our work VQ-Flows: Vector Quantized Local Normalizing Flows has been accepted to
|Jan 19, 2022||
Our work Machine Learning Methods Trained on Simple Models can Anticipate Crtitical Transitions in Complex Systems has been accepted to the
|Oct 24, 2021||
Our work Task Attended Meta-Learning for Few-Shot Learning has been accepted to the
|May 10, 2021||
Our work On Characterizing GAN Convergence Through Proximal Duality Gap has been accepted to
|Apr 10, 2021||
Our work On Duality Gap as a Measure for Monitoring GAN Training has been accepted to the
On Characterizing GAN Convergence Through Proximal Duality GapIn Proceedings of the 38th International Conference on Machine Learning (ICML) 2021
Task Attended Meta-Learning for Few-Shot LearningIn Fifth Workshop on Meta-Learning at the Conference on Neural Information Processing Systems (NeurIPS) 2021
Stress Testing of Meta-learning Approaches for Few-shot LearningIn AAAI Workshop on Metalearning and Co-Hosted Challenge 2021
On Duality Gap as a Measure for Monitoring GAN TrainingIn International Joint Conference on Neural Networks (IJCNN) 2021