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.


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.

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,

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.

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