Pascanu, Razvan

110 publications

TMLR 2026 TRecViT: A Recurrent Video Transformer Viorica Patraucean, Xu Owen He, Joseph Heyward, Chuhan Zhang, Mehdi S. M. Sajjadi, George-Cristian Muraru, Artem Zholus, Mahdi Karami, Ross Goroshin, Yutian Chen, Simon Osindero, Joao Carreira, Razvan Pascanu

ICML 2025 A Large Recurrent Action Model: xLSTM Enables Fast Inference for Robotics Tasks Thomas Schmied, Thomas Adler, Vihang Prakash Patil, Maximilian Beck, Korbinian Pöppel, Johannes Brandstetter, Günter Klambauer, Razvan Pascanu, Sepp Hochreiter

ICLR 2025 Attention as a Hypernetwork Simon Schug, Seijin Kobayashi, Yassir Akram, Joao Sacramento, Razvan Pascanu

ICLRW 2025 From Markov to Laplace: How Mamba In-Context Learns Markov Chains Marco Bondaschi, Nived Rajaraman, Xiuying Wei, Kannan Ramchandran, Razvan Pascanu, Caglar Gulcehre, Michael Gastpar, Ashok Vardhan Makkuva

ICLRW 2025 MS-SSM: A Multi-Scale State Space Model for Enhanced Sequence Modeling Mahdi Karami, Ali Behrouz, Peilin Zhong, Razvan Pascanu, Vahab Mirrokni

TMLR 2025 Maxwell's Demon at Work: Efficient Pruning by Leveraging Saturation of Neurons Simon Dufort-Labbé, Pierluca D'Oro, Evgenii Nikishin, Irina Rish, Pierre-Luc Bacon, Razvan Pascanu, Aristide Baratin

NeurIPS 2025 Meta-Learning How to Share Credit Among Macro-Actions Ionel Hosu, Traian Rebedea, Razvan Pascanu

NeurIPS 2025 Plasticity as the Mirror of Empowerment David Abel, Michael Bowling, Andre Barreto, Will Dabney, Shi Dong, Steven Stenberg Hansen, Anna Harutyunyan, Khimya Khetarpal, Clare Lyle, Razvan Pascanu, Georgios Piliouras, Doina Precup, Jonathan Richens, Mark Rowland, Tom Schaul, Satinder Singh

NeurIPS 2025 RAT: Bridging RNN Efficiency and Attention Accuracy via Chunk-Based Sequence Modeling Xiuying Wei, Anunay Yadav, Razvan Pascanu, Caglar Gulcehre

ICLR 2025 Round and Round We Go! What Makes Rotary Positional Encodings Useful? Federico Barbero, Alex Vitvitskyi, Christos Perivolaropoulos, Razvan Pascanu, Petar Veličković

ICML 2025 SoftMax Is Not Enough (for Sharp Size Generalisation) Petar Veličković, Christos Perivolaropoulos, Federico Barbero, Razvan Pascanu

NeurIPSW 2024 A Large Recurrent Action Model: xLSTM Enables Fast Inference for Robotics Tasks Thomas Schmied, Thomas Adler, Vihang Prakash Patil, Maximilian Beck, Korbinian Pöppel, Johannes Brandstetter, Günter Klambauer, Razvan Pascanu, Sepp Hochreiter

NeurIPS 2024 Building on Efficient Foundations: Effective Training of LLMs with Structured Feedforward Layers Xiuying Wei, Skander Moalla, Razvan Pascanu, Caglar Gulcehre

TMLR 2024 Continual Learning: Applications and the Road Forward Eli Verwimp, Rahaf Aljundi, Shai Ben-David, Matthias Bethge, Andrea Cossu, Alexander Gepperth, Tyler L. Hayes, Eyke Hüllermeier, Christopher Kanan, Dhireesha Kudithipudi, Christoph H. Lampert, Martin Mundt, Razvan Pascanu, Adrian Popescu, Andreas S. Tolias, Joost van de Weijer, Bing Liu, Vincenzo Lomonaco, Tinne Tuytelaars, Gido M van de Ven

ICLR 2024 Discovering Modular Solutions That Generalize Compositionally Simon Schug, Seijin Kobayashi, Yassir Akram, Maciej Wolczyk, Alexandra Maria Proca, Johannes von Oswald, Razvan Pascanu, Joao Sacramento, Angelika Steger

CoLLAs 2024 Disentangling the Causes of Plasticity Loss in Neural Networks Clare Lyle, Zeyu Zheng, Khimya Khetarpal, Hado van Hasselt, Razvan Pascanu, James Martens, Will Dabney

ICML 2024 Fine-Tuning Reinforcement Learning Models Is Secretly a Forgetting Mitigation Problem Maciej Wolczyk, Bartłomiej Cupiał, Mateusz Ostaszewski, Michał Bortkiewicz, Michał Zając, Razvan Pascanu, Łukasz Kuciński, Piotr Miłoś

ICML 2024 Improving Fine-Grained Understanding in Image-Text Pre-Training Ioana Bica, Anastasija Ilic, Matthias Bauer, Goker Erdogan, Matko Bošnjak, Christos Kaplanis, Alexey A. Gritsenko, Matthias Minderer, Charles Blundell, Razvan Pascanu, Jovana Mitrovic

ICLR 2024 Kalman Filter for Online Classification of Non-Stationary Data Michalis Titsias, Alexandre Galashov, Amal Rannen-Triki, Razvan Pascanu, Yee Whye Teh, Jorg Bornschein

NeurIPS 2024 No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO Skander Moalla, Andrea Miele, Daniil Pyatko, Razvan Pascanu, Caglar Gulcehre

ICMLW 2024 No Representation, No Trust: Connecting Representation, Collapse, and Trust Issues in PPO Skander Moalla, Andrea Miele, Razvan Pascanu, Caglar Gulcehre

NeurIPS 2024 Non-Stationary Learning of Neural Networks with Automatic Soft Parameter Reset Alexandre Galashov, Michalis K. Titsias, András György, Clare Lyle, Razvan Pascanu, Yee Whye Teh, Maneesh Sahani

NeurIPS 2024 Normalization and Effective Learning Rates in Reinforcement Learning Clare Lyle, Zeyu Zheng, Khimya Khetarpal, James Martens, Hado van Hasselt, Razvan Pascanu, Will Dabney

TMLR 2024 Promoting Exploration in Memory-Augmented Adam Using Critical Momenta Pranshu Malviya, Goncalo Mordido, Aristide Baratin, Reza Babanezhad Harikandeh, Jerry Huang, Simon Lacoste-Julien, Razvan Pascanu, Sarath Chandar

NeurIPSW 2024 SoftMax Is Not Enough (For Sharp Out-of-Distribution) Petar Veličković, Christos Perivolaropoulos, Federico Barbero, Razvan Pascanu

NeurIPSW 2024 SoftMax Is Not Enough (For Sharp Out-of-Distribution) Petar Veličković, Christos Perivolaropoulos, Federico Barbero, Razvan Pascanu

NeurIPS 2024 Transformers Need Glasses! Information Over-Squashing in Language Tasks Federico Barbero, Andrea Banino, Steven Kapturowski, Dharshan Kumaran, João G.M. Araújo, Alex Vitvitskyi, Razvan Pascanu, Petar Veličković

ICMLW 2024 Transformers Need Glasses! Information Over-Squashing in Language Tasks Federico Barbero, Andrea Banino, Steven Kapturowski, Dharshan Kumaran, João Guilherme Madeira Araújo, Alex Vitvitskyi, Razvan Pascanu, Petar Veličković

ICML 2024 Universality of Linear Recurrences Followed by Non-Linear Projections: Finite-Width Guarantees and Benefits of Complex Eigenvalues Antonio Orvieto, Soham De, Caglar Gulcehre, Razvan Pascanu, Samuel L Smith

ICMLW 2023 Asynchronous Algorithmic Alignment with Cocycles Andrew Joseph Dudzik, Tamara von Glehn, Razvan Pascanu, Petar Veličković

LoG 2023 Asynchronous Algorithmic Alignment with Cocycles Andrew Joseph Dudzik, Tamara Glehn, Razvan Pascanu, Petar Veličković

CoLLAs 2023 Continually Learning Representations at Scale Alexandre Galashov, Jovana Mitrovic, Dhruva Tirumala, Yee Whye Teh, Timothy Nguyen, Arslan Chaudhry, Razvan Pascanu

NeurIPS 2023 Deep Reinforcement Learning with Plasticity Injection Evgenii Nikishin, Junhyuk Oh, Georg Ostrovski, Clare Lyle, Razvan Pascanu, Will Dabney, Andre Barreto

ICLRW 2023 Deep Reinforcement Learning with Plasticity Injection Evgenii Nikishin, Junhyuk Oh, Georg Ostrovski, Clare Lyle, Razvan Pascanu, Will Dabney, Andre Barreto

LoG 2023 Latent Space Representations of Neural Algorithmic Reasoners Vladimir V Mirjanic, Razvan Pascanu, Petar Veličković

NeurIPS 2023 Learning to Modulate Pre-Trained Models in RL Thomas Schmied, Markus Hofmarcher, Fabian Paischer, Razvan Pascanu, Sepp Hochreiter

ICLRW 2023 Learning to Modulate Pre-Trained Models in RL Thomas Schmied, Markus Hofmarcher, Fabian Paischer, Razvan Pascanu, Sepp Hochreiter

JMLR 2023 Nevis'22: A Stream of 100 Tasks Sampled from 30 Years of Computer Vision Research Jorg Bornschein, Alexandre Galashov, Ross Hemsley, Amal Rannen-Triki, Yutian Chen, Arslan Chaudhry, Xu Owen He, Arthur Douillard, Massimo Caccia, Qixuan Feng, Jiajun Shen, Sylvestre-Alvise Rebuffi, Kitty Stacpoole, Diego de las Casas, Will Hawkins, Angeliki Lazaridou, Yee Whye Teh, Andrei A. Rusu, Razvan Pascanu, Marc’Aurelio Ranzato

ICLRW 2023 On the Role of Forgetting in Fine-Tuning Reinforcement Learning Models Maciej Wolczyk, Bartłomiej Cupiał, Michał Zając, Razvan Pascanu, Łukasz Kuciński, Piotr Miłoś

ICLR 2023 Pre-Training via Denoising for Molecular Property Prediction Sheheryar Zaidi, Michael Schaarschmidt, James Martens, Hyunjik Kim, Yee Whye Teh, Alvaro Sanchez-Gonzalez, Peter Battaglia, Razvan Pascanu, Jonathan Godwin

ICML 2023 Resurrecting Recurrent Neural Networks for Long Sequences Antonio Orvieto, Samuel L Smith, Albert Gu, Anushan Fernando, Caglar Gulcehre, Razvan Pascanu, Soham De

NeurIPSW 2023 Revisiting Dynamic Evaluation: Online Adaptation for Large Language Models Amal Rannen-Triki, Jorg Bornschein, Razvan Pascanu, Alexandre Galashov, Michalis Titsias, Marcus Hutter, András György, Yee Whye Teh

ICLR 2023 SemPPL: Predicting Pseudo-Labels for Better Contrastive Representations Matko Bošnjak, Pierre Harvey Richemond, Nenad Tomasev, Florian Strub, Jacob C Walker, Felix Hill, Lars Holger Buesing, Razvan Pascanu, Charles Blundell, Jovana Mitrovic

NeurIPSW 2023 Stochastic Linear Dynamics in Parameters to Deal with Neural Networks Plasticity Loss Alexandre Galashov, Michalis Titsias, Razvan Pascanu, Yee Whye Teh, Maneesh Sahani

NeurIPS 2023 The Tunnel Effect: Building Data Representations in Deep Neural Networks Wojciech Masarczyk, Mateusz Ostaszewski, Ehsan Imani, Razvan Pascanu, Piotr Miłoś, Tomasz Trzcinski

ICML 2023 Understanding Plasticity in Neural Networks Clare Lyle, Zeyu Zheng, Evgenii Nikishin, Bernardo Avila Pires, Razvan Pascanu, Will Dabney

TMLR 2022 An Empirical Study of Implicit Regularization in Deep Offline RL Caglar Gulcehre, Srivatsan Srinivasan, Jakub Sygnowski, Georg Ostrovski, Mehrdad Farajtabar, Matthew Hoffman, Razvan Pascanu, Arnaud Doucet

JMLR 2022 Behavior Priors for Efficient Reinforcement Learning Dhruva Tirumala, Alexandre Galashov, Hyeonwoo Noh, Leonard Hasenclever, Razvan Pascanu, Jonathan Schwarz, Guillaume Desjardins, Wojciech Marian Czarnecki, Arun Ahuja, Yee Whye Teh, Nicolas Heess

NeurIPS 2022 Disentangling Transfer in Continual Reinforcement Learning Maciej Wolczyk, Michał Zając, Razvan Pascanu, Łukasz Kuciński, Piotr Miłoś

NeurIPSW 2022 Pre-Training via Denoising for Molecular Property Prediction Sheheryar Zaidi, Michael Schaarschmidt, James Martens, Hyunjik Kim, Yee Whye Teh, Alvaro Sanchez-Gonzalez, Peter Battaglia, Razvan Pascanu, Jonathan Godwin

CoLLAs 2022 Probing Transfer in Deep Reinforcement Learning Without Task Engineering Andrei Alex Rusu, Sebastian Flennerhag, Dushyant Rao, Razvan Pascanu, Raia Hadsell

ICMLW 2022 Pushing the Limits of Self-Supervised ResNets: Can We Outperform Supervised Learning Without Labels on ImageNet? Nenad Tomasev, Ioana Bica, Brian McWilliams, Lars Holger Buesing, Razvan Pascanu, Charles Blundell, Jovana Mitrovic

LoG 2022 Reasoning-Modulated Representations Petar Veličković, Matko Bošnjak, Thomas Kipf, Alexander Lerchner, Raia Hadsell, Razvan Pascanu, Charles Blundell

CoLLAs 2022 Test Sample Accuracy Scales with Training Sample Density in Neural Networks Xu Ji, Razvan Pascanu, R. Devon Hjelm, Balaji Lakshminarayanan, Andrea Vedaldi

ICML 2022 The CLRS Algorithmic Reasoning Benchmark Petar Veličković, Adrià Puigdomènech Badia, David Budden, Razvan Pascanu, Andrea Banino, Misha Dashevskiy, Raia Hadsell, Charles Blundell

LoG 2022 The First Learning on Graphs Conference: Preface Bastian Rieck, Razvan Pascanu, Yuanqi Du, Hannes Stärk, Derek Lim, Chaitanya K. Joshi, Andreea Deac, Iulia Duta, Joshua Robinson, Gabriele Corso, Leonardo Cotta, Yanqiao Zhu, Kexin Huang, Michelle Li, Sofia Bourhim, Ilia Igashov

NeurIPSW 2022 When Does Re-Initialization Work? Sheheryar Zaidi, Tudor Berariu, Hyunjik Kim, Jorg Bornschein, Claudia Clopath, Yee Whye Teh, Razvan Pascanu

ICML 2022 Wide Neural Networks Forget Less Catastrophically Seyed Iman Mirzadeh, Arslan Chaudhry, Dong Yin, Huiyi Hu, Razvan Pascanu, Dilan Gorur, Mehrdad Farajtabar

NeurIPS 2021 Continual World: A Robotic Benchmark for Continual Reinforcement Learning Maciej Wołczyk, Michał Zając, Razvan Pascanu, Łukasz Kuciński, Piotr Miłoś

ICLR 2021 Linear Mode Connectivity in Multitask and Continual Learning Seyed Iman Mirzadeh, Mehrdad Farajtabar, Dilan Gorur, Razvan Pascanu, Hassan Ghasemzadeh

NeurIPS 2021 On the Role of Optimization in Double Descent: A Least Squares Study Ilja Kuzborskij, Csaba Szepesvari, Omar Rivasplata, Amal Rannen-Triki, Razvan Pascanu

NeurIPS 2021 Powerpropagation: A Sparsity Inducing Weight Reparameterisation Jonathan Schwarz, Siddhant Jayakumar, Razvan Pascanu, Peter E Latham, Yee W. Teh

ICML 2021 Spectral Normalisation for Deep Reinforcement Learning: An Optimisation Perspective Florin Gogianu, Tudor Berariu, Mihaela C Rosca, Claudia Clopath, Lucian Busoniu, Razvan Pascanu

ICMLW 2021 Task-Agnostic Continual Learning with Hybrid Probabilistic Models Polina Kirichenko, Mehrdad Farajtabar, Dushyant Rao, Balaji Lakshminarayanan, Nir Levine, Ang Li, Huiyi Hu, Andrew Gordon Wilson, Razvan Pascanu

ICLR 2020 Functional Regularisation for Continual Learning with Gaussian Processes Michalis K. Titsias, Jonathan Schwarz, Alexander G. de G. Matthews, Razvan Pascanu, Yee Whye Teh

ICML 2020 Improving the Gating Mechanism of Recurrent Neural Networks Albert Gu, Caglar Gulcehre, Thomas Paine, Matt Hoffman, Razvan Pascanu

ICLR 2020 Meta-Learning with Warped Gradient Descent Sebastian Flennerhag, Andrei A. Rusu, Razvan Pascanu, Francesco Visin, Hujun Yin, Raia Hadsell

ICLR 2020 Multiplicative Interactions and Where to Find Them Siddhant M. Jayakumar, Wojciech M. Czarnecki, Jacob Menick, Jonathan Schwarz, Jack Rae, Simon Osindero, Yee Whye Teh, Tim Harley, Razvan Pascanu

NeurIPS 2020 Pointer Graph Networks Petar Veličković, Lars Buesing, Matthew Overlan, Razvan Pascanu, Oriol Vinyals, Charles Blundell

ICML 2020 Stabilizing Transformers for Reinforcement Learning Emilio Parisotto, Francis Song, Jack Rae, Razvan Pascanu, Caglar Gulcehre, Siddhant Jayakumar, Max Jaderberg, Raphaël Lopez Kaufman, Aidan Clark, Seb Noury, Matthew Botvinick, Nicolas Heess, Raia Hadsell

ICMLW 2020 Task Agnostic Continual Learning via Meta Learning Xu He, Jakub Sygnowski, Alexandre Galashov, Andrei Alex Rusu, Yee Whye Teh, Razvan Pascanu

NeurIPS 2020 Top-KAST: Top-K Always Sparse Training Siddhant Jayakumar, Razvan Pascanu, Jack Rae, Simon Osindero, Erich Elsen

NeurIPS 2020 Understanding the Role of Training Regimes in Continual Learning Seyed Iman Mirzadeh, Mehrdad Farajtabar, Razvan Pascanu, Hassan Ghasemzadeh

ICLRW 2019 A RAD Approach to Deep Mixture Models Laurent Dinh, Jascha Sohl-Dickstein, Razvan Pascanu, Hugo Larochelle

NeurIPS 2019 Continual Unsupervised Representation Learning Dushyant Rao, Francesco Visin, Andrei Rusu, Razvan Pascanu, Yee Whye Teh, Raia Hadsell

ICLR 2019 Deep Reinforcement Learning with Relational Inductive Biases Vinicius Zambaldi, David Raposo, Adam Santoro, Victor Bapst, Yujia Li, Igor Babuschkin, Karl Tuyls, David Reichert, Timothy Lillicrap, Edward Lockhart, Murray Shanahan, Victoria Langston, Razvan Pascanu, Matthew Botvinick, Oriol Vinyals, Peter Battaglia

AISTATS 2019 Distilling Policy Distillation Wojciech M. Czarnecki, Razvan Pascanu, Simon Osindero, Siddhant Jayakumar, Grzegorz Swirszcz, Max Jaderberg

ICLR 2019 Hyperbolic Attention Networks Caglar Gulcehre, Misha Denil, Mateusz Malinowski, Ali Razavi, Razvan Pascanu, Karl Moritz Hermann, Peter Battaglia, Victor Bapst, David Raposo, Adam Santoro, Nando de Freitas

ICLR 2019 Information Asymmetry in KL-Regularized RL Alexandre Galashov, Siddhant M. Jayakumar, Leonard Hasenclever, Dhruva Tirumala, Jonathan Schwarz, Guillaume Desjardins, Wojciech M. Czarnecki, Yee Whye Teh, Razvan Pascanu, Nicolas Heess

ICLR 2019 Meta-Learning with Latent Embedding Optimization Andrei A. Rusu, Dushyant Rao, Jakub Sygnowski, Oriol Vinyals, Razvan Pascanu, Simon Osindero, Raia Hadsell

ICML 2018 Been There, Done That: Meta-Learning with Episodic Recall Samuel Ritter, Jane Wang, Zeb Kurth-Nelson, Siddhant Jayakumar, Charles Blundell, Razvan Pascanu, Matthew Botvinick

ICLR 2018 Memory-Based Parameter Adaptation Pablo Sprechmann, Siddhant M. Jayakumar, Jack W. Rae, Alexander Pritzel, Adria Puigdomenech Badia, Benigno Uria, Oriol Vinyals, Demis Hassabis, Razvan Pascanu, Charles Blundell

ICML 2018 Mix & Match Agent Curricula for Reinforcement Learning Wojciech Czarnecki, Siddhant Jayakumar, Max Jaderberg, Leonard Hasenclever, Yee Whye Teh, Nicolas Heess, Simon Osindero, Razvan Pascanu

ICLR 2018 Model Compression via Distillation and Quantization Antonio Polino, Razvan Pascanu, Dan Alistarh

ICML 2018 Progress & Compress: A Scalable Framework for Continual Learning Jonathan Schwarz, Wojciech Czarnecki, Jelena Luketina, Agnieszka Grabska-Barwinska, Yee Whye Teh, Razvan Pascanu, Raia Hadsell

NeurIPS 2018 Relational Recurrent Neural Networks Adam Santoro, Ryan Faulkner, David Raposo, Jack Rae, Mike Chrzanowski, Theophane Weber, Daan Wierstra, Oriol Vinyals, Razvan Pascanu, Timothy Lillicrap

NeurIPS 2017 A Simple Neural Network Module for Relational Reasoning Adam Santoro, David Raposo, David G Barrett, Mateusz Malinowski, Razvan Pascanu, Peter Battaglia, Timothy Lillicrap

ICLR 2017 Discovering Objects and Their Relations from Entangled Scene Representations David Raposo, Adam Santoro, David G. T. Barrett, Razvan Pascanu, Tim Lillicrap, Peter W. Battaglia

NeurIPS 2017 Distral: Robust Multitask Reinforcement Learning Yee Teh, Victor Bapst, Wojciech M. Czarnecki, John Quan, James Kirkpatrick, Raia Hadsell, Nicolas Heess, Razvan Pascanu

NeurIPS 2017 Imagination-Augmented Agents for Deep Reinforcement Learning Sébastien Racanière, Theophane Weber, David Reichert, Lars Buesing, Arthur Guez, Danilo Jimenez Rezende, Adrià Puigdomènech Badia, Oriol Vinyals, Nicolas Heess, Yujia Li, Razvan Pascanu, Peter Battaglia, Demis Hassabis, David Silver, Daan Wierstra

ICLR 2017 Learning to Navigate in Complex Environments Piotr Mirowski, Razvan Pascanu, Fabio Viola, Hubert Soyer, Andy Ballard, Andrea Banino, Misha Denil, Ross Goroshin, Laurent Sifre, Koray Kavukcuoglu, Dharshan Kumaran, Raia Hadsell

ICLR 2017 Metacontrol for Adaptive Imagination-Based Optimization Jessica B. Hamrick, Andrew J. Ballard, Razvan Pascanu, Oriol Vinyals, Nicolas Heess, Peter W. Battaglia

ICML 2017 Sharp Minima Can Generalize for Deep Nets Laurent Dinh, Razvan Pascanu, Samy Bengio, Yoshua Bengio

CoRL 2017 Sim-to-Real Robot Learning from Pixels with Progressive Nets Andrei A. Rusu, Matej Vecerík, Thomas Rothörl, Nicolas Heess, Razvan Pascanu, Raia Hadsell

NeurIPS 2017 Sobolev Training for Neural Networks Wojciech M. Czarnecki, Simon Osindero, Max Jaderberg, Grzegorz Swirszcz, Razvan Pascanu

NeurIPS 2017 Visual Interaction Networks: Learning a Physics Simulator from Video Nicholas Watters, Daniel Zoran, Theophane Weber, Peter Battaglia, Razvan Pascanu, Andrea Tacchetti

NeurIPS 2016 Interaction Networks for Learning About Objects, Relations and Physics Peter Battaglia, Razvan Pascanu, Matthew Lai, Danilo Jimenez Rezende, Koray Kavukcuoglu

ICLR 2016 Policy Distillation Andrei A. Rusu, Sergio Gomez Colmenarejo, Çaglar Gülçehre, Guillaume Desjardins, James Kirkpatrick, Razvan Pascanu, Volodymyr Mnih, Koray Kavukcuoglu, Raia Hadsell

NeurIPS 2015 Natural Neural Networks Guillaume Desjardins, Karen Simonyan, Razvan Pascanu, Koray Kavukcuoglu

ICLR 2014 How to Construct Deep Recurrent Neural Networks Razvan Pascanu, Çaglar Gülçehre, Kyunghyun Cho, Yoshua Bengio

NeurIPS 2014 Identifying and Attacking the Saddle Point Problem in High-Dimensional Non-Convex Optimization Yann N. Dauphin, Razvan Pascanu, Caglar Gulcehre, Kyunghyun Cho, Surya Ganguli, Yoshua Bengio

ECML-PKDD 2014 Learned-Norm Pooling for Deep Feedforward and Recurrent Neural Networks Çaglar Gülçehre, KyungHyun Cho, Razvan Pascanu, Yoshua Bengio

ICLR 2014 On the Number of Inference Regions of Deep Feed Forward Networks with Piece-Wise Linear Activations Razvan Pascanu, Guido Montúfar, Yoshua Bengio

NeurIPS 2014 On the Number of Linear Regions of Deep Neural Networks Guido F. Montufar, Razvan Pascanu, Kyunghyun Cho, Yoshua Bengio

ICLR 2014 Revisiting Natural Gradient for Deep Networks Razvan Pascanu, Yoshua Bengio

ICLR 2013 Metric-Free Natural Gradient for Joint-Training of Boltzmann Machines Guillaume Desjardins, Razvan Pascanu, Aaron C. Courville, Yoshua Bengio

ICLR 2013 Natural Gradient Revisited Razvan Pascanu, Yoshua Bengio

ICML 2013 On the Difficulty of Training Recurrent Neural Networks Razvan Pascanu, Tomas Mikolov, Yoshua Bengio

JMLR 2012 Learning Algorithms for the Classification Restricted Boltzmann Machine Hugo Larochelle, Michael Mandel, Razvan Pascanu, Yoshua Bengio

AISTATS 2011 Deep Learners Benefit More from Out-of-Distribution Examples Yoshua Bengio, Frédéric Bastien, Arnaud Bergeron, Nicolas Boulanger–Lewandowski, Thomas Breuel, Youssouf Chherawala, Moustapha Cisse, Myriam Côté, Dumitru Erhan, Jeremy Eustache, Xavier Glorot, Xavier Muller, Sylvain Pannetier Lebeuf, Razvan Pascanu, Salah Rifai, François Savard, Guillaume Sicard