Andreas Look - RankMe

19 papers A* 1A 2B 1C 1Journal 13

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Don't double it: Efficient Agent Prediction in Occlusions. CoRR Anna Rothenhäusler, Markus Mazzola, Andreas Look, Raghu Rajan, Joschka Bödecker
2026	J	`jnl`	Uncertainty Matters: Structured Probabilistic Online Mapping for Motion Prediction in Autonomous Driving. CoRR Pritom Gogoi, Faris Janjos, Bin Yang, Andreas Look
2025	A*	`conf`	Motion Forecasting via Model-Based Risk Minimization. ICRA Aron Distelzweig, Eitan Kosman, Andreas Look, Faris Janjos, Denesh K. Manivannan, Abhinav Valada
2025	A	`conf`	Stochasticity in Motion: An Information-Theoretic Approach to Trajectory Prediction. IROS Aron Distelzweig, Andreas Look, Eitan Kosman, Faris Janjos, Jörg Wagner, Abhinav Valada
2024	J	`jnl`	Entropy-Based Uncertainty Modeling for Trajectory Prediction in Autonomous Driving. CoRR Aron Distelzweig, Andreas Look, Eitan Kosman, Faris Janjos, Jörg Wagner, Abhinav Valada
2024	J	`jnl`	Motion Forecasting via Model-Based Risk Minimization. CoRR Aron Distelzweig, Eitan Kosman, Andreas Look, Faris Janjos, Denesh K. Manivannan, Abhinav Valada
2023	J	`jnl`	A Deterministic Approximation to Neural SDEs. IEEE Trans. Pattern Anal. Mach. Intell. Andreas Look, Melih Kandemir, Barbara Rakitsch, Jan Peters
2023	J	`jnl`	Can you text what is happening? Integrating pre-trained language encoders into trajectory prediction models for autonomous driving. CoRR Ali Keysan, Andreas Look, Eitan Kosman, Gonca Gürsun, Jörg Wagner, Yu Yao, Barbara Rakitsch
2023	J	`jnl`	Cheap and Deterministic Inference for Deep State-Space Models of Interacting Dynamical Systems. CoRR Andreas Look, Melih Kandemir, Barbara Rakitsch, Jan Peters
2023	J	`jnl`	Cheap and Deterministic Inference for Deep State-Space Models of Interacting Dynamical Systems. Trans. Mach. Learn. Res. Andreas Look, Barbara Rakitsch, Melih Kandemir, Jan Peters
2023	—	`—`	Deterministic Approximations for Deep State-Space Models. Andreas Look
2023	J	`jnl`	Sampling-Free Probabilistic Deep State-Space Models. CoRR Andreas Look, Melih Kandemir, Barbara Rakitsch, Jan Peters
2021	A	`conf`	Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes. AISTATS Manuel Haußmann, Sebastian Gerwinn, Andreas Look, Barbara Rakitsch, Melih Kandemir
2020	J	`jnl`	Deterministic Inference of Neural Stochastic Differential Equations. CoRR Andreas Look, Chen Qiu, Maja Rudolph, Jan Peters, Melih Kandemir
2020	J	`jnl`	Differentiable Implicit Layers. CoRR Andreas Look, Simona Doneva, Melih Kandemir, Rainer Gemulla, Jan Peters
2020	J	`jnl`	Learning Partially Known Stochastic Dynamics with Empirical PAC Bayes. CoRR Manuel Haußmann, Sebastian Gerwinn, Andreas Look, Barbara Rakitsch, Melih Kandemir
2019	B	`conf`	Dealing with Limited Access to Data: Comparison of Deep Learning Approaches. IJCNN Andreas Look, Stefan Riedelbauch
2019	J	`jnl`	Differential Bayesian Neural Nets. CoRR Andreas Look, Melih Kandemir
2018	C	`conf`	Building Robust Classifiers with Generative Adversarial Networks for Detecting Cavitation in Hydraulic Turbines. ICPRAM Andreas Look, Oliver Kirschner, Stefan Riedelbauch