Justin Bayer - RankMe

55 papers A* 4A 5C 1Misc 2Journal 27Unranked 15

Year	Rank	Type	Title / Venue / Authors
2025	J	`jnl`	Inherently Robust Control through Maximum-Entropy Learning-Based Rollout. Trans. Mach. Learn. Res. Felix Bok, Atanas Mirchev, Baris Kayalibay, Ole Jonas Wenzel, Patrick van der Smagt, Justin Bayer
2024	Misc	`conf`	Exploring Under Constraints with Model-Based Actor-Critic and Safety Filters. CoRL Ahmed Agha, Baris Kayalibay, Atanas Mirchev, Patrick van der Smagt, Justin Bayer
2023	—	`conf`	Filter-Aware Model-Predictive Control. L4DC Baris Kayalibay, Atanas Mirchev, Ahmed Agha, Patrick van der Smagt, Justin Bayer
2023	J	`jnl`	Filter-Aware Model-Predictive Control. CoRR Baris Kayalibay, Atanas Mirchev, Ahmed Agha, Patrick van der Smagt, Justin Bayer
2022	Misc	`conf`	PRISM: Probabilistic Real-Time Inference in Spatial World Models. CoRL Atanas Mirchev, Baris Kayalibay, Ahmed Agha, Patrick van der Smagt, Daniel Cremers, Justin Bayer
2022	J	`jnl`	PRISM: Probabilistic Real-Time Inference in Spatial World Models. CoRR Atanas Mirchev, Baris Kayalibay, Ahmed Agha, Patrick van der Smagt, Daniel Cremers, Justin Bayer
2022	—	`conf`	Tracking and Planning with Spatial World Models. L4DC Baris Kayalibay, Atanas Mirchev, Patrick van der Smagt, Justin Bayer
2022	J	`jnl`	Tracking and Planning with Spatial World Models. CoRR Baris Kayalibay, Atanas Mirchev, Patrick van der Smagt, Justin Bayer
2021	A*	`conf`	Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models. ICLR Justin Bayer, Maximilian Soelch, Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt
2021	J	`jnl`	Mind the Gap when Conditioning Amortised Inference in Sequential Latent-Variable Models. CoRR Justin Bayer, Maximilian Soelch, Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt
2021	A*	`conf`	Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF. ICLR Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt, Justin Bayer
2020	A*	`conf`	Learning Flat Latent Manifolds with VAEs. ICML Nutan Chen, Alexej Klushyn, Francesco Ferroni, Justin Bayer, Patrick van der Smagt
2020	J	`jnl`	Learning Flat Latent Manifolds with VAEs. CoRR Nutan Chen, Alexej Klushyn, Francesco Ferroni, Justin Bayer, Patrick van der Smagt
2020	J	`jnl`	Variational State-Space Models for Localisation and Dense 3D Mapping in 6 DoF. CoRR Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt, Justin Bayer
2019	—	`conf`	Approximate Bayesian Inference in Spatial Environments. Robotics: Science and Systems Atanas Mirchev, Baris Kayalibay, Maximilian Soelch, Patrick van der Smagt, Justin Bayer
2019	A	`conf`	Bayesian Learning of Neural Network Architectures. AISTATS Georgi Dikov, Justin Bayer
2019	J	`jnl`	Bayesian Learning of Neural Network Architectures. CoRR Georgi Dikov, Patrick van der Smagt, Justin Bayer
2019	—	`conf`	Fast Approximate Geodesics for Deep Generative Models. ICANN (2) Nutan Chen, Francesco Ferroni, Alexej Klushyn, Alexandros Paraschos, Justin Bayer, Patrick van der Smagt
2019	—	`conf`	Increasing the Generalisaton Capacity of Conditional VAEs. ICANN (2) Alexej Klushyn, Nutan Chen, Botond Cseke, Justin Bayer, Patrick van der Smagt
2019	J	`jnl`	Increasing the Generalisaton Capacity of Conditional VAEs. CoRR Alexej Klushyn, Nutan Chen, Botond Cseke, Justin Bayer, Patrick van der Smagt
2019	—	`conf`	On Deep Set Learning and the Choice of Aggregations. ICANN (1) Maximilian Soelch, Adnan Akhundov, Patrick van der Smagt, Justin Bayer
2019	J	`jnl`	On Deep Set Learning and the Choice of Aggregations. CoRR Maximilian Soelch, Adnan Akhundov, Patrick van der Smagt, Justin Bayer
2019	C	`conf`	Unsupervised Real-Time Control Through Variational Empowerment. ISRR Maximilian Karl, Philip Becker-Ehmck, Maximilian Soelch, Djalel Benbouzid, Patrick van der Smagt, Justin Bayer
2019	J	`jnl`	Variational Tracking and Prediction with Generative Disentangled State-Space Models. CoRR Adnan Akhundov, Maximilian Soelch, Justin Bayer, Patrick van der Smagt
2018	J	`jnl`	Approximate Bayesian inference in spatial environments. CoRR Atanas Mirchev, Baris Kayalibay, Patrick van der Smagt, Justin Bayer
2018	J	`jnl`	Fast Approximate Geodesics for Deep Generative Models. CoRR Nutan Chen, Francesco Ferroni, Alexej Klushyn, Alexandros Paraschos, Justin Bayer, Patrick van der Smagt
2018	A	`conf`	Metrics for Deep Generative Models. AISTATS Nutan Chen, Alexej Klushyn, Richard Kurle, Xueyan Jiang, Justin Bayer, Patrick van der Smagt
2017	—	`conf`	Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data. ICLR (Poster) Maximilian Karl, Maximilian Soelch, Justin Bayer, Patrick van der Smagt
2017	J	`jnl`	Key Insights into Hand Biomechanics: Human Grip Stiffness Can Be Decoupled from Force by Cocontraction and Predicted from Electromyography. Frontiers Neurorobotics Hannes Höppner, Maximilian Große-Dunker, Georg Stillfried, Justin Bayer, Patrick van der Smagt
2017	J	`jnl`	Metrics for Deep Generative Models. CoRR Nutan Chen, Alexej Klushyn, Richard Kurle, Xueyan Jiang, Justin Bayer, Patrick van der Smagt
2016	J	`jnl`	Deep Variational Bayes Filters: Unsupervised Learning of State Space Models from Raw Data. CoRR Maximilian Karl, Maximilian Soelch, Justin Bayer, Patrick van der Smagt
2016	J	`jnl`	ML-based tactile sensor calibration: A universal approach. CoRR Maximilian Karl, Artur Lohrer, Dhananjay Shah, Frederik Diehl, Max Fiedler, Saahil Ognawala, Justin Bayer, Patrick van der Smagt
2016	J	`jnl`	Theano: A Python framework for fast computation of mathematical expressions. CoRR 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
2016	J	`jnl`	Unsupervised preprocessing for Tactile Data. CoRR Maximilian Karl, Justin Bayer, Patrick van der Smagt
2016	J	`jnl`	Variational Inference for On-line Anomaly Detection in High-Dimensional Time Series. CoRR Maximilian Soelch, Justin Bayer, Marvin Ludersdorfer, Patrick van der Smagt
2015	J	`jnl`	Efficient Empowerment. CoRR Maximilian Karl, Justin Bayer, Patrick van der Smagt
2015	—	`conf`	Efficient movement representation by embedding Dynamic Movement Primitives in deep autoencoders. Humanoids Nutan Chen, Justin Bayer, Sebastian Urban, Patrick van der Smagt
2015	J	`jnl`	Fast Adaptive Weight Noise. CoRR Justin Bayer, Maximilian Karl, Daniela Korhammer, Patrick van der Smagt
2015	—	`—`	Learning Sequence Representations. Justin Bayer
2015	A	`conf`	Measuring fingertip forces from camera images for random finger poses. IROS Nutan Chen, Sebastian Urban, Justin Bayer, Patrick van der Smagt
2014	A*	`conf`	Estimating finger grip force from an image of the hand using Convolutional Neural Networks and Gaussian processes. ICRA Nutan Chen, Sebastian Urban, Christian Osendorfer, Justin Bayer, Patrick van der Smagt
2014	J	`jnl`	Learning Stochastic Recurrent Networks. CoRR Justin Bayer, Christian Osendorfer
2014	—	`conf`	On Fast Dropout and its Applicability to Recurrent Networks. ICLR (Poster) Justin Bayer, Christian Osendorfer, Nutan Chen, Sebastian Urban, Patrick van der Smagt
2014	J	`jnl`	Regularizing Recurrent Networks - On Injected Noise and Norm-based Methods. CoRR Saahil Ognawala, Justin Bayer
2013	A	`conf`	Computing grip force and torque from finger nail images using Gaussian processes. IROS Sebastian Urban, Justin Bayer, Christian Osendorfer, Göran Westling, Benoni B. Edin, Patrick van der Smagt
2013	A	`conf`	Continuous robot control using surface electromyography of atrophic muscles. IROS Jörn Vogel, Justin Bayer, Patrick van der Smagt
2013	—	`conf`	Convolutional Neural Networks Learn Compact Local Image Descriptors. ICONIP (3) Christian Osendorfer, Justin Bayer, Sebastian Urban, Patrick van der Smagt
2013	J	`jnl`	Convolutional Neural Networks learn compact local image descriptors CoRR Christian Osendorfer, Justin Bayer, Patrick van der Smagt
2013	—	`conf`	Training Neural Networks with Implicit Variance. ICONIP (2) Justin Bayer, Christian Osendorfer, Sebastian Urban, Patrick van der Smagt
2013	—	`conf`	Unsupervised Feature Learning for low-level Local Image Descriptors ICLR (Workshop Poster) Christian Osendorfer, Justin Bayer, Patrick van der Smagt
2012	—	`conf`	Identification of Human Limb Stiffness in 5 DoF and Estimation via EMG. ISER Dominic Lakatos, Daniel Rüschen, Justin Bayer, Jörn Vogel, Patrick van der Smagt
2012	—	`conf`	Learning Sequence Neighbourhood Metrics. ICANN (1) Justin Bayer, Christian Osendorfer, Patrick van der Smagt
2011	J	`jnl`	Learning Sequence Neighbourhood Metrics CoRR Justin Bayer, Christian Osendorfer, Patrick van der Smagt
2010	J	`jnl`	PyBrain. J. Mach. Learn. Res. Tom Schaul, Justin Bayer, Daan Wierstra, Yi Sun, Martin Felder, Frank Sehnke, Thomas Rückstieß, Jürgen Schmidhuber
2009	—	`conf`	Evolving Memory Cell Structures for Sequence Learning. ICANN (2) Justin Bayer, Daan Wierstra, Julian Togelius, Jürgen Schmidhuber