Justin Bayer

Publication Activity (10 Years)

Years Active: 2009-2023
Publications (10 Years): 37

Top Venues

CoRR

IROS

ICLR (Poster)

ICANN (2)

Technical University Munich (PHD)

Education History

Technical University Munich

PHD

Publications

Baris Kayalibay, Atanas Mirchev, Ahmed Agha, Patrick van der Smagt, Justin Bayer
Filter-Aware Model-Predictive Control. CoRR (2023)
Baris Kayalibay, Atanas Mirchev, Ahmed Agha, Patrick van der Smagt, Justin Bayer
Filter-Aware Model-Predictive Control. L4DC (2023)
Atanas Mirchev, Baris Kayalibay, Ahmed Agha, Patrick van der Smagt, Daniel Cremers, Justin Bayer
PRISM: Probabilistic Real-Time Inference in Spatial World Models. CoRL (2022)
Baris Kayalibay, Atanas Mirchev, Patrick van der Smagt, Justin Bayer
Tracking and Planning with Spatial World Models. L4DC (2022)
Baris Kayalibay, Atanas Mirchev, Patrick van der Smagt, Justin Bayer
Tracking and Planning with Spatial World Models. CoRR (2022)
Atanas Mirchev, Baris Kayalibay, Ahmed Agha, Patrick van der Smagt, Daniel Cremers, Justin Bayer
PRISM: Probabilistic Real-Time Inference in Spatial World Models. CoRR (2022)
Justin Bayer, Maximilian Soelch, Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt
Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models. ICLR (2021)
Justin Bayer, Maximilian Soelch, Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt
Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models. CoRR (2021)
Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt, Justin Bayer
Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF. ICLR (2021)
Nutan Chen, Alexej Klushyn, Francesco Ferroni, Justin Bayer, Patrick van der Smagt
Learning Flat Latent Manifolds with VAEs. CoRR (2020)
Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt, Justin Bayer
Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF. CoRR (2020)
Nutan Chen, Alexej Klushyn, Francesco Ferroni, Justin Bayer, Patrick van der Smagt
Learning Flat Latent Manifolds with VAEs. ICML (2020)
Maximilian Soelch, Adnan Akhundov, Patrick van der Smagt, Justin Bayer
On Deep Set Learning and the Choice of Aggregations. ICANN (1) (2019)
Maximilian Soelch, Adnan Akhundov, Patrick van der Smagt, Justin Bayer
On Deep Set Learning and the Choice of Aggregations. CoRR (2019)
Alexej Klushyn, Nutan Chen, Botond Cseke, Justin Bayer, Patrick van der Smagt
Increasing the Generalisaton Capacity of Conditional VAEs. ICANN (2) (2019)
Georgi Dikov, Patrick van der Smagt, Justin Bayer
Bayesian Learning of Neural Network Architectures. CoRR (2019)
Adnan Akhundov, Maximilian Soelch, Justin Bayer, Patrick van der Smagt
Variational Tracking and Prediction with Generative Disentangled State-Space Models. CoRR (2019)
Alexej Klushyn, Nutan Chen, Botond Cseke, Justin Bayer, Patrick van der Smagt
Increasing the Generalisaton Capacity of Conditional VAEs. CoRR (2019)
Atanas Mirchev, Baris Kayalibay, Maximilian Soelch, Patrick van der Smagt, Justin Bayer
Approximate Bayesian Inference in Spatial Environments. Robotics: Science and Systems (2019)
Nutan Chen, Francesco Ferroni, Alexej Klushyn, Alexandros Paraschos, Justin Bayer, Patrick van der Smagt
Fast Approximate Geodesics for Deep Generative Models. ICANN (2) (2019)
Georgi Dikov, Justin Bayer
Bayesian Learning of Neural Network Architectures. AISTATS (2019)
Maximilian Karl, Philip Becker-Ehmck, Maximilian Soelch, Djalel Benbouzid, Patrick van der Smagt, Justin Bayer
Unsupervised Real-Time Control Through Variational Empowerment. ISRR (2019)
Nutan Chen, Francesco Ferroni, Alexej Klushyn, Alexandros Paraschos, Justin Bayer, Patrick van der Smagt
Fast Approximate Geodesics for Deep Generative Models. CoRR (2018)
Nutan Chen, Alexej Klushyn, Richard Kurle, Xueyan Jiang, Justin Bayer, Patrick van der Smagt
Metrics for Deep Generative Models. AISTATS (2018)
Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt, Justin Bayer
Approximate Bayesian inference in spatial environments. CoRR (2018)
Nutan Chen, Alexej Klushyn, Richard Kurle, Xueyan Jiang, Justin Bayer, Patrick van der Smagt
Metrics for Deep Generative Models. CoRR (2017)
Hannes Höppner, Maximilian Große-Dunker, Georg Stillfried, Justin Bayer, Patrick van der Smagt
Key Insights into Hand Biomechanics: Human Grip Stiffness Can Be Decoupled from Force by Cocontraction and Predicted from Electromyography. Frontiers Neurorobotics 11 (2017)
Maximilian Karl, Maximilian Soelch, Justin Bayer, Patrick van der Smagt
Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data. ICLR (Poster) (2017)
Maximilian Karl, Artur Lohrer, Dhananjay Shah, Frederik Diehl, Max Fiedler, Saahil Ognawala, Justin Bayer, Patrick van der Smagt
ML-based tactile sensor calibration: A universal approach. CoRR (2016)
Maximilian Karl, Maximilian Soelch, Justin Bayer, Patrick van der Smagt
Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data. CoRR (2016)
Rami Al-Rfou, Guillaume Alain, Amjad Almahairi, Christof Angermüller, Dzmitry Bahdanau, Nicolas Ballas, Frédéric Bastien, Justin Bayer, Anatoly Belikov, Alexander Belopolsky, Yoshua Bengio, Arnaud Bergeron, James Bergstra, Valentin Bisson, Josh Bleecher Snyder, Nicolas Bouchard, Nicolas Boulanger-Lewandowski, Xavier Bouthillier, Alexandre de Brébisson, Olivier Breuleux, Pierre Luc Carrier, Kyunghyun Cho, Jan Chorowski, Paul F. Christiano, Tim Cooijmans, Marc-Alexandre Côté, Myriam Côté, Aaron C. Courville, Yann N. Dauphin, Olivier Delalleau, Julien Demouth, Guillaume Desjardins, Sander Dieleman, Laurent Dinh, Melanie Ducoffe, Vincent Dumoulin, Samira Ebrahimi Kahou, Dumitru Erhan, Ziye Fan, Orhan Firat, Mathieu Germain, Xavier Glorot, Ian J. Goodfellow, Matthew Graham, Çaglar Gülçehre, Philippe Hamel, Iban Harlouchet, Jean-Philippe Heng, Balázs Hidasi, Sina Honari, Arjun Jain, Sébastien Jean, Kai Jia, Mikhail Korobov, Vivek Kulkarni, Alex Lamb, Pascal Lamblin, Eric Larsen, César Laurent, Sean Lee, Simon Lefrançois, Simon Lemieux, Nicholas Léonard, Zhouhan Lin, Jesse A. Livezey, Cory Lorenz, Jeremiah Lowin, Qianli Ma, Pierre-Antoine Manzagol, Olivier Mastropietro, Robert McGibbon, Roland Memisevic, Bart van Merriënboer, Vincent Michalski, Mehdi Mirza, Alberto Orlandi, Christopher Joseph Pal, Razvan Pascanu, Mohammad Pezeshki, Colin Raffel, Daniel Renshaw, Matthew Rocklin, Adriana Romero, Markus Roth, Peter Sadowski, John Salvatier, François Savard, Jan Schlüter, John Schulman, Gabriel Schwartz, Iulian Vlad Serban, Dmitriy Serdyuk, Samira Shabanian, Étienne Simon, Sigurd Spieckermann, S. Ramana Subramanyam, Jakub Sygnowski, Jérémie Tanguay, Gijs van Tulder, Joseph P. Turian, Sebastian Urban, Pascal Vincent, Francesco Visin, Harm de Vries, David Warde-Farley, Dustin J. Webb, Matthew Willson, Kelvin Xu, Lijun Xue, Li Yao, Saizheng Zhang, Ying Zhang
Theano: A Python framework for fast computation of mathematical expressions. CoRR (2016)
Maximilian Soelch, Justin Bayer, Marvin Ludersdorfer, Patrick van der Smagt
Variational Inference for On-line Anomaly Detection in High-Dimensional Time Series. CoRR (2016)
Maximilian Karl, Justin Bayer, Patrick van der Smagt
Unsupervised preprocessing for Tactile Data. CoRR (2016)
Maximilian Karl, Justin Bayer, Patrick van der Smagt
Efficient Empowerment. CoRR (2015)
Justin Bayer, Maximilian Karl, Daniela Korhammer, Patrick van der Smagt
Fast Adaptive Weight Noise. CoRR (2015)
Nutan Chen, Sebastian Urban, Justin Bayer, Patrick van der Smagt
Measuring fingertip forces from camera images for random finger poses. IROS (2015)
Nutan Chen, Justin Bayer, Sebastian Urban, Patrick van der Smagt
Efficient movement representation by embedding Dynamic Movement Primitives in deep autoencoders. Humanoids (2015)
Justin Bayer, Christian Osendorfer, Nutan Chen, Sebastian Urban, Patrick van der Smagt
On Fast Dropout and its Applicability to Recurrent Networks. ICLR (Poster) (2014)
Saahil Ognawala, Justin Bayer
Regularizing Recurrent Networks - On Injected Noise and Norm-based Methods. CoRR (2014)
Justin Bayer, Christian Osendorfer
Learning Stochastic Recurrent Networks. CoRR (2014)
Nutan Chen, Sebastian Urban, Christian Osendorfer, Justin Bayer, Patrick van der Smagt
Estimating finger grip force from an image of the hand using Convolutional Neural Networks and Gaussian processes. ICRA (2014)
Justin Bayer, Christian Osendorfer, Sebastian Urban, Patrick van der Smagt
Training Neural Networks with Implicit Variance. ICONIP (2) (2013)
Christian Osendorfer, Justin Bayer, Patrick van der Smagt
Convolutional Neural Networks learn compact local image descriptors CoRR (2013)
Christian Osendorfer, Justin Bayer, Sebastian Urban, Patrick van der Smagt
Convolutional Neural Networks Learn Compact Local Image Descriptors. ICONIP (3) (2013)
Sebastian Urban, Justin Bayer, Christian Osendorfer, Göran Westling, Benoni B. Edin, Patrick van der Smagt
Computing grip force and torque from finger nail images using Gaussian processes. IROS (2013)
Jörn Vogel, Justin Bayer, Patrick van der Smagt
Continuous robot control using surface electromyography of atrophic muscles. IROS (2013)
Christian Osendorfer, Justin Bayer, Patrick van der Smagt
Unsupervised Feature Learning for low-level Local Image Descriptors ICLR (Workshop Poster) (2013)
Justin Bayer, Christian Osendorfer, Patrick van der Smagt
Learning Sequence Neighbourhood Metrics. ICANN (1) (2012)
Dominic Lakatos, Daniel Rüschen, Justin Bayer, Jörn Vogel, Patrick van der Smagt
Identification of Human Limb Stiffness in 5 DoF and Estimation via EMG. ISER (2012)
Justin Bayer, Christian Osendorfer, Patrick van der Smagt
Learning Sequence Neighbourhood Metrics CoRR (2011)
Tom Schaul, Justin Bayer, Daan Wierstra, Yi Sun, Martin Felder, Frank Sehnke, Thomas Rückstieß, Jürgen Schmidhuber
PyBrain. J. Mach. Learn. Res. 11 (2010)
Justin Bayer, Daan Wierstra, Julian Togelius, Jürgen Schmidhuber
Evolving Memory Cell Structures for Sequence Learning. ICANN (2) (2009)

Justin Bayer.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Justin Bayer