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Cheap and Deterministic Inference for Deep State-Space Models of
  Interacting Dynamical Systems

Cheap and Deterministic Inference for Deep State-Space Models of Interacting Dynamical Systems

2 May 2023
Andreas Look
M. Kandemir
Barbara Rakitsch
Jan Peters
    BDL
ArXivPDFHTML

Papers citing "Cheap and Deterministic Inference for Deep State-Space Models of Interacting Dynamical Systems"

6 / 6 papers shown
Title
Motion Forecasting via Model-Based Risk Minimization
Motion Forecasting via Model-Based Risk Minimization
Aron Distelzweig
Eitan Kosman
Andreas Look
Faris Janjoš
Denesh K. Manivannan
Abhinav Valada
34
3
0
16 Sep 2024
Sampling-Free Probabilistic Deep State-Space Models
Sampling-Free Probabilistic Deep State-Space Models
Andreas Look
M. Kandemir
Barbara Rakitsch
Jan Peters
16
2
0
15 Sep 2023
Can you text what is happening? Integrating pre-trained language
  encoders into trajectory prediction models for autonomous driving
Can you text what is happening? Integrating pre-trained language encoders into trajectory prediction models for autonomous driving
Ali Keysan
Andreas Look
Eitan Kosman
Gonca Gürsun
Jörg Wagner
Yu Yao
Barbara Rakitsch
24
29
0
11 Sep 2023
Implicit Latent Variable Model for Scene-Consistent Motion Forecasting
Implicit Latent Variable Model for Scene-Consistent Motion Forecasting
Sergio Casas
Cole Gulino
Simon Suo
Katie Z Luo
Renjie Liao
R. Urtasun
161
155
0
23 Jul 2020
Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction
Discrete Residual Flow for Probabilistic Pedestrian Behavior Prediction
Ajay Jain
Sergio Casas
Renjie Liao
Yuwen Xiong
Song Feng
Sean Segal
R. Urtasun
149
73
0
17 Oct 2019
Dropout as a Bayesian Approximation: Representing Model Uncertainty in
  Deep Learning
Dropout as a Bayesian Approximation: Representing Model Uncertainty in Deep Learning
Y. Gal
Zoubin Ghahramani
UQCV
BDL
285
9,138
0
06 Jun 2015
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