I am a PhD student at the Max Planck Institut für Informatik, Saarbrücken, advised by Dr. Bernt Schiele and Dr. Mario Fritz. My research interests lie in the areas of Generative Models, Bayesian Inference and their applictaion to the area of Autonomous Driving. Previously, I completed my Master’s Thesis at Saarland University under the supervision of Dr. Jilles Vreeken in the area of Algorithmic Data Mining and my Bachelors degree at the National Institute of Technology, Karnataka, India.

Publications

europvi Euro-PVI: Pedestrian Vehicle Interactions in Dense Urban Centers,
Computer Vision and Pattern Recognition (CVPR), 2021.
Coming Soon



marscf Normalizing Flows with Multi-scale Autoregressive Priors,
Computer Vision and Pattern Recognition (CVPR), 2020.
Paper | Workshop Extension | Code | Video



hbaflow Haar Wavelet based Block Autoregressive Flows for Trajectories,
German Conference on Pattern Recognition, 2020 (oral).
Paper | Video



upleak Updates-Leak: Data Set Inference and Reconstruction Attacks in Online Learning,
USENIX Security Symposium (USENIX Security), 2020.
Paper



cfvae Conditional Flow Variational Autoencoders for Structured Sequence Prediction,
BDL@NeurIPS’19 and ML4AD@NeurIPS’19 (oral).
Paper | Video



bmsvaegan “Best-of-Many-Samples” Distribution Matching,
BDL@NeurIPS’19.
Paper



synlikelihood Bayesian Prediction of Future Street Scenes using Synthetic Likelihoods,
International Conference on Learning Representations (ICLR), 2019.
Paper | Code + Data



bmscvae Accurate and Diverse Sampling of Sequences based on a “Best of Many” Sample Objective,
Computer Vision and Pattern Recognition (CVPR), 2018 (oral).
Paper | Code



longtermonboard Long-Term On-Board Prediction of People in Traffic Scenes under Uncertainty,
Computer Vision and Pattern Recognition (CVPR), 2018.
Paper | Code + Data



boundary Long-Term Image Boundary Prediction,
AAAI Conference on Artificial Intelligence, 2018.
Paper



squish Efficiently Summarising Event Sequences with Rich Interleaving Patterns,
SIAM International Conference on Data Mining (SDM), 2017.
Paper