Roland Memisevic

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 30

Top Topics

Machine Translation

Top Venues

Publications

Sunny Panchal, Apratim Bhattacharyya, Guillaume Berger, Antoine Mercier, Cornelius Böhm, Florian Dietrichkeit, Reza Pourreza, Xuanlin Li, Pulkit Madan, Mingu Lee, Mark Todorovich, Ingo Bax, Roland Memisevic
Live Fitness Coaching as a Testbed for Situated Interaction. CoRR (2024)
Apratim Bhattacharyya, Sunny Panchal, Reza Pourreza, Mingu Lee, Pulkit Madan, Roland Memisevic
Look, Remember and Reason: Grounded Reasoning in Videos with Language Models. ICLR (2024)
Antoine Mercier, Guillaume Berger, Sunny Panchal, Florian Letsch, Cornelius Boehm, Nahua Kang, Ingo Bax, Roland Memisevic
Is end-to-end learning enough for fitness activity recognition? CoRR (2023)
Reza Pourreza, Apratim Bhattacharyya, Sunny Panchal, Mingu Lee, Pulkit Madan, Roland Memisevic
Painter: Teaching Auto-regressive Language Models to Draw Sketches. CoRR (2023)
Zhan Ling, Yunhao Fang, Xuanlin Li, Zhiao Huang, Mingu Lee, Roland Memisevic, Hao Su
Deductive Verification of Chain-of-Thought Reasoning. NeurIPS (2023)
Reza Pourreza, Apratim Bhattacharyya, Sunny Panchal, Mingu Lee, Pulkit Madan, Roland Memisevic
Painter: Teaching Auto-regressive Language Models to Draw Sketches. ICCV (Workshops) (2023)
Apratim Bhattacharyya, Sunny Panchal, Mingu Lee, Reza Pourreza, Pulkit Madan, Roland Memisevic
Look, Remember and Reason: Visual Reasoning with Grounded Rationales. CoRR (2023)
Zhan Ling, Yunhao Fang, Xuanlin Li, Tongzhou Mu, Mingu Lee, Reza Pourreza, Roland Memisevic, Hao Su
Unleashing the Creative Mind: Language Model As Hierarchical Policy For Improved Exploration on Challenging Problem Solving. CoRR (2023)
Zhan Ling, Yunhao Fang, Xuanlin Li, Zhiao Huang, Mingu Lee, Roland Memisevic, Hao Su
Deductive Verification of Chain-of-Thought Reasoning. CoRR (2023)
Roland Memisevic
Metaphors We Learn By. CoRR (2022)
Joanna Materzynska, Guillaume Berger, Ingo Bax, Roland Memisevic
The Jester Dataset: A Large-Scale Video Dataset of Human Gestures. ICCV Workshops (2019)
Farzaneh Mahdisoltani, Roland Memisevic, David J. Fleet
Hierarchical Video Understanding. CoRR (2018)
Farzaneh Mahdisoltani, Guillaume Berger, Waseem Gharbieh, David J. Fleet, Roland Memisevic
Fine-grained Video Classification and Captioning. CoRR (2018)
Raghav Goyal, Farzaneh Mahdisoltani, Guillaume Berger, Waseem Gharbieh, Ingo Bax, Roland Memisevic
Evaluating visual "common sense" using fine-grained classification and captioning tasks. ICLR (Workshop) (2018)
Farzaneh Mahdisoltani, Roland Memisevic, David J. Fleet
Hierarchical Video Understanding. ECCV Workshops (4) (2018)
Samira Ebrahimi Kahou, Vincent Michalski, Roland Memisevic, Christopher Joseph Pal, Pascal Vincent
RATM: Recurrent Attentive Tracking Model. CVPR Workshops (2017)
Raghav Goyal, Samira Ebrahimi Kahou, Vincent Michalski, Joanna Materzynska, Susanne Westphal, Heuna Kim, Valentin Haenel, Ingo Fründ, Peter Yianilos, Moritz Mueller-Freitag, Florian Hoppe, Christian Thurau, Ingo Bax, Roland Memisevic
The "something something" video database for learning and evaluating visual common sense. CoRR (2017)
Raghav Goyal, Samira Ebrahimi Kahou, Vincent Michalski, Joanna Materzynska, Susanne Westphal, Heuna Kim, Valentin Haenel, Ingo Fründ, Peter Yianilos, Moritz Mueller-Freitag, Florian Hoppe, Christian Thurau, Ingo Bax, Roland Memisevic
The "Something Something" Video Database for Learning and Evaluating Visual Common Sense. ICCV (2017)
Guillaume Berger, Roland Memisevic
Incorporating long-range consistency in CNN-based texture generation. ICLR (Poster) (2017)
Daniel Jiwoong Im, Sungjin Ahn, Roland Memisevic, Yoshua Bengio
Denoising Criterion for Variational Auto-Encoding Framework. AAAI (2017)
Zhouhan Lin, Matthieu Courbariaux, Roland Memisevic, Yoshua Bengio
Neural Networks with Few Multiplications. ICLR (2016)
Saizheng Zhang, Yuhuai Wu, Tong Che, Zhouhan Lin, Roland Memisevic, Ruslan Salakhutdinov, Yoshua Bengio
Architectural Complexity Measures of Recurrent Neural Networks. NIPS (2016)
Harm de Vries, Roland Memisevic, Aaron C. Courville
Deep Learning Vector Quantization. ESANN (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)
Daniel Jiwoong Im, Mohamed Ishmael Diwan Belghazi, Roland Memisevic
Conservativeness of Untied Auto-Encoders. AAAI (2016)
Samira Ebrahimi Kahou, Xavier Bouthillier, Pascal Lamblin, Çaglar Gülçehre, Vincent Michalski, Kishore Konda, Sébastien Jean, Pierre Froumenty, Yann N. Dauphin, Nicolas Boulanger-Lewandowski, Raul Chandias Ferrari, Mehdi Mirza, David Warde-Farley, Aaron C. Courville, Pascal Vincent, Roland Memisevic, Christopher Joseph Pal, Yoshua Bengio
EmoNets: Multimodal deep learning approaches for emotion recognition in video. J. Multimodal User Interfaces 10 (2) (2016)
Guillaume Berger, Roland Memisevic
Incorporating long-range consistency in CNN-based texture generation. CoRR (2016)
David Krueger, Roland Memisevic
Regularizing RNNs by Stabilizing Activations. ICLR (2016)
Saizheng Zhang, Yuhuai Wu, Tong Che, Zhouhan Lin, Roland Memisevic, Ruslan Salakhutdinov, Yoshua Bengio
Architectural Complexity Measures of Recurrent Neural Networks. CoRR (2016)
Daniel Jiwoong Im, Chris Dongjoo Kim, Hui Jiang, Roland Memisevic
Generating images with recurrent adversarial networks. CoRR (2016)
Daniel Jiwoong Im, Sungjin Ahn, Roland Memisevic, Yoshua Bengio
Denoising Criterion for Variational Auto-Encoding Framework. CoRR (2015)
Hanna Kamyshanska, Roland Memisevic
The Potential Energy of an Autoencoder. IEEE Trans. Pattern Anal. Mach. Intell. 37 (6) (2015)
Samira Ebrahimi Kahou, Vincent Michalski, Roland Memisevic
RATM: Recurrent Attentive Tracking Model. CoRR (2015)
Kishore Reddy Konda, Roland Memisevic
Learning Visual Odometry with a Convolutional Network. VISAPP (1) (2015)
Sébastien Jean, Orhan Firat, Kyunghyun Cho, Roland Memisevic, Yoshua Bengio
Montreal Neural Machine Translation Systems for WMT'15. WMT@EMNLP (2015)
Roland Memisevic, Kishore Reddy Konda, David Krueger
Zero-bias autoencoders and the benefits of co-adapting features. ICLR (Poster) (2015)
Sébastien Jean, KyungHyun Cho, Roland Memisevic, Yoshua Bengio
On Using Very Large Target Vocabulary for Neural Machine Translation. ACL (1) (2015)
Zhouhan Lin, Roland Memisevic, Kishore Reddy Konda
How far can we go without convolution: Improving fully-connected networks. CoRR (2015)
Kishore Reddy Konda, Xavier Bouthillier, Roland Memisevic, Pascal Vincent
Dropout as data augmentation. CoRR (2015)
Samira Ebrahimi Kahou, Vincent Michalski, Kishore Reddy Konda, Roland Memisevic, Christopher Joseph Pal
Recurrent Neural Networks for Emotion Recognition in Video. ICMI (2015)
Daniel Jiwoong Im, Mohamed Ishmael Diwan Belghazi, Roland Memisevic
Conservativeness of untied auto-encoders. CoRR (2015)
Samira Ebrahimi Kahou, Xavier Bouthillier, Pascal Lamblin, Çaglar Gülçehre, Vincent Michalski, Kishore Reddy Konda, Sébastien Jean, Pierre Froumenty, Yann N. Dauphin, Nicolas Boulanger-Lewandowski, Raul Chandias Ferrari, Mehdi Mirza, David Warde-Farley, Aaron C. Courville, Pascal Vincent, Roland Memisevic, Christopher J. Pal, Yoshua Bengio
EmoNets: Multimodal deep learning approaches for emotion recognition in video. CoRR (2015)
Kishore Konda, Pramod Chandrashekhariah, Roland Memisevic, Jochen Triesch
Real-time activity recognition via deep learning of motion features. ESANN (2015)
Roland Memisevic
Deep learning: Architectures, algorithms, applications. Hot Chips Symposium (2015)
Vincent Michalski, Roland Memisevic, Kishore Reddy Konda
Modeling Deep Temporal Dependencies with Recurrent "Grammar Cells". NIPS (2014)
Vincent Michalski, Roland Memisevic, Kishore Reddy Konda
Modeling sequential data using higher-order relational features and predictive training. CoRR (2014)
Kishore Reddy Konda, Roland Memisevic, Vincent Michalski
The role of spatio-temporal synchrony in the encoding of motion. ICLR (Poster) (2014)
Kishore Reddy Konda, Roland Memisevic
A unified approach to learning depth and motion features. ICVGIP (2014)
Sébastien Jean, Kyunghyun Cho, Roland Memisevic, Yoshua Bengio
On Using Very Large Target Vocabulary for Neural Machine Translation. CoRR (2014)
Roland Memisevic
Learning to Relate Images. IEEE Trans. Pattern Anal. Mach. Intell. 35 (8) (2013)
Kishore Reddy Konda, Roland Memisevic
Unsupervised learning of depth and motion. CoRR (2013)
Roland Memisevic, Georgios Exarchakis
Learning invariant features by harnessing the aperture problem. ICML (3) (2013)
Felix Bauer, Roland Memisevic
Feature grouping from spatially constrained multiplicative interaction ICLR (2013)
Hanna Kamyshanska, Roland Memisevic
On autoencoder scoring. ICML (3) (2013)
Samira Ebrahimi Kahou, Christopher J. Pal, Xavier Bouthillier, Pierre Froumenty, Çaglar Gülçehre, Roland Memisevic, Pascal Vincent, Aaron C. Courville, Yoshua Bengio, Raul Chandias Ferrari, Mehdi Mirza, Sébastien Jean, Pierre Luc Carrier, Yann N. Dauphin, Nicolas Boulanger-Lewandowski, Abhishek Aggarwal, Jeremie Zumer, Pascal Lamblin, Jean-Philippe Raymond, Guillaume Desjardins, Razvan Pascanu, David Warde-Farley, Atousa Torabi, Arjun Sharma, Emmanuel Bengio, Kishore Reddy Konda, Zhenzhou Wu
Combining modality specific deep neural networks for emotion recognition in video. ICMI (2013)
Roland Memisevic
On multi-view feature learning. ICML (2012)
Roland Memisevic, Leonid Sigal, David J. Fleet
Shared Kernel Information Embedding for Discriminative Inference. IEEE Trans. Pattern Anal. Mach. Intell. 34 (4) (2012)
Roland Memisevic
On multi-view feature learning CoRR (2012)
Roland Memisevic
Learning to relate images: Mapping units, complex cells and simultaneous eigenspaces CoRR (2011)
Roland Memisevic
Gradient-based learning of higher-order image features. ICCV (2011)
Joshua M. Susskind, Geoffrey E. Hinton, Roland Memisevic, Marc Pollefeys
Modeling the joint density of two images under a variety of transformations. CVPR (2011)
Roland Memisevic, Christopher Zach, Geoffrey E. Hinton, Marc Pollefeys
Gated Softmax Classification. NIPS (2010)
Roland Memisevic, Geoffrey E. Hinton
Learning to Represent Spatial Transformations with Factored Higher-Order Boltzmann Machines. Neural Comput. 22 (6) (2010)
Leonid Sigal, Roland Memisevic, David J. Fleet
Shared Kernel Information Embedding for discriminative inference. CVPR (2009)
Roland Memisevic, Geoffrey E. Hinton
Unsupervised Learning of Image Transformations. CVPR (2007)
Horst Samulowitz, Roland Memisevic
Learning to Solve QBF. AAAI (2007)
Roland Memisevic
Kernel information embeddings. ICML (2006)
Peter Meinicke, Stefan Klanke, Roland Memisevic, Helge J. Ritter
Principal Surfaces from Unsupervised Kernel Regression. IEEE Trans. Pattern Anal. Mach. Intell. 27 (9) (2005)
Roland Memisevic, Geoffrey E. Hinton
Improving dimensionality reduction with spectral gradient descent. Neural Networks 18 (5-6) (2005)
Roland Memisevic, Geoffrey E. Hinton
Multiple Relational Embedding. NIPS (2004)