Technische Universität München
Publikationen und Poster
J. Y. Tee, O. De Candido, W. Utschick, and P. Geiger, 09/2023, On Learning the Tail Quantiles of Driving Behavior Distributions via Quantile Regression and Flows, 26th IEEE International Conference on Intelligent Transportation Systems ITSC 2023; Bilbao, Bizkaia, Spain
M. Henneberg, C. Eghtebas, O. De Candido, K. Kunze, and J. A. Ward, 04/2023, Detecting an Offset-Adjusted Similarity Score based on Duchenne Smiles, CHI EA '23: Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems; Hamburg, Germany, 10.1145/3544549.3585709
K. Klein, O. De Candido, and W. Utschick, 07/2023, Interpretable Classifiers based on Time-Series Motifs for Lane Change Prediction, IEEE Transactions on Intelligent Vehicles, Volume: 8, Issue: 7, 10.1109/TIV.2023.3276650
Oliver De Candido, Michael Koller, Wolfgang Utschick, 04/2022, Encouraging Validatable Features in Machine Learning-based Highly Automated Driving Functions, IEEE Transactions on Intelligent Vehicles, DOI:10.1109/TIV.2022.3171215
Oliver De Candido, Xinyang Li, Wolfgang Utschick, 06/2022, An Analysis of Distributional Shifts in Automated Driving Functions in Highway Scenarios, Helsinki, Finland, DOI:10.1109/VTC2022-Spring54318.2022.9860453
Philipp Joppich, Sebastian Dorn, Oliver De Candido, Jakob Knollmüller, Wolfgang Utschick, 07/2022, Classification and Uncertainty Quantification of Corrupted Data Using Supervised Autoencoders, Paris, France, 41st International Workshop on Bayesian Inference and Maximum Entropy Methods in Science and Engineering, DOI:10.3390/psf2022005012
Tobias Uelwer, Felix Michels, Oliver De Candido, 12/2022, Evaluating Robust Perceptual Losses for Image Reconstruction, New Orleans, USA, NeurIPS 2022, I Can't Believe It's Not Better Workshop: Understanding Deep Learning Through Empirical Falsification
De Candido, O.; Binder, M.; Utschick, W., 07/2021, An Interpretable Lane Change Detector Algorithm based on Deep Autoencoder Anomaly Detection, 2021 IEEE Intelligent Vehicles Symposium (IV), Nagoya, Japan (Onlinekonferenz), DOI: 10.1109/IV48863.2021.9575599, peer-reviewed
Gallitz O., De Candido O., Botsch M., Utschick W., 09/2021, Interpretable Early Prediction of Lane Changes Using a Constrained Neural Network Architecture, 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), Indianapolis, IN, USA (Onlinekonferenz), DOI: 10.1109/itsc48978.2021.9564555, peer-reviewed
Joppich, Philipp; Dorn, Sebastian; De Candido, Oliver; Utschick, Wolfgang; Knollmüller, Jakob, 05/2021, Classification and Uncertainty Quantification of Corrupted Data using Semi-Supervised Autoencoders, arXiv preprint arXiv:2105.13393
Konstantinidis Fabian; Hofmann Ulrich; Sackmann Moritz; Thielecke Jorn; De Candido Oliver; Utschick Wolfgang, 09/2021, Parameter Sharing Reinforcement Learning for Modeling Multi-Agent Driving Behavior in Roundabout Scenarios, 2021 IEEE International Intelligent Transportation Systems Conference (ITSC), Indianapolis, IN, USA (Onlinekonferenz), DOI: 10.1109/itsc48978.2021.9565031, peer-reviewed
Uelwer Tobias; Michels Felix; De Candido Oliver, 09/2021, Learning to Detect Adversarial Examples Based on Class Scores, KI 2021: Advances in Artificial Intelligence, Onlinekonferenz, DOI: 10.1007/978-3-030-87626-5_17, peer-reviewed
De Candido, O., Gallitz, O., Melz, R., Botsch, M., Utschick,W., 10/2020, Interpretable Machine Learning Structure for an Early Prediction of Lane Changes, Onlinekonferenz: Artificial Neural Networks and Machine Learning – ICANN 2020. DOI: 10.1007/978-3-030-61609-0_27, peer-reviewed
De Candido, O., Koller, M., Gallitz, O., Melz, R., Botsch, M., Utschick,W., 2020, Towards Feature Validation in Time to Lane Change Classification using Deep Neural Networks. Sep. 20-23, 2020, The 23rd IEEE Intelligent Transportation Systems Conference (ITSC). DOI: 10.1109/ITSC45102.2020.9294555, peer-reviewed
Gallitz, O., De Candido, O., Melz, R., Botsch, M., Utschick,W., 2020, Interpretable Machine Learning Structure for an Early Prediction of Lane Changes.ICANN (1): 337-349
K. Klein, O. De Candido, and W. Utschick, 07/2023, Interpretable Classifiers based on Time-Series Motifs for Lane Change Prediction, IEEE Transactions on Intelligent Vehicles, Volume: 8, Issue: 7, 10.1109/TIV.2023.3276650