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Panel Discussion1
Razvan Pascanu · Irina Rish
Author Information
Razvan Pascanu (DeepMind)
Irina Rish (MILA / Université de Montréal h)
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2022 : Towards Out-of-Distribution Adversarial Robustness »
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2022 : Pushing the limits of self-supervised ResNets: Can we outperform supervised learning without labels on ImageNet? »
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2023 : On the Universality of Linear Recurrences Followed by Nonlinear Projections »
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2023 : Towards Out-of-Distribution Adversarial Robustness »
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2023 : Maximum State Entropy Exploration using Predecessor and Successor Representations »
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2023 : Latent Space Representations of Neural Algorithmic Reasoners »
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2023 : Asynchronous Algorithmic Alignment with Cocycles »
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2023 : Continual Pre-Training of Large Language Models: How to re-warm your model? »
Kshitij Gupta · Benjamin Thérien · Adam Ibrahim · Mats Richter · Quentin Anthony · Eugene Belilovsky · Timothée Lesort · Irina Rish -
2023 : Cognitive Models as Simulators: Using Cognitive Models to Tap into Implicit Human Feedback »
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2023 : Asynchronous Algorithmic Alignment with Cocycles »
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2023 Oral: Resurrecting Recurrent Neural Networks for Long Sequences »
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2023 Oral: Understanding Plasticity in Neural Networks »
Clare Lyle · Zeyu Zheng · Evgenii Nikishin · Bernardo Avila Pires · Razvan Pascanu · Will Dabney -
2023 Poster: Understanding Plasticity in Neural Networks »
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2023 Poster: Resurrecting Recurrent Neural Networks for Long Sequences »
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2022 Poster: Wide Neural Networks Forget Less Catastrophically »
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2022 Spotlight: Wide Neural Networks Forget Less Catastrophically »
Seyed Iman Mirzadeh · Arslan Chaudhry · Dong Yin · Huiyi Hu · Razvan Pascanu · Dilan Gorur · Mehrdad Farajtabar -
2022 Poster: The CLRS Algorithmic Reasoning Benchmark »
Petar Veličković · Adrià Puigdomenech Badia · David Budden · Razvan Pascanu · Andrea Banino · Misha Dashevskiy · Raia Hadsell · Charles Blundell -
2022 Spotlight: The CLRS Algorithmic Reasoning Benchmark »
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2022 Poster: Towards Scaling Difference Target Propagation by Learning Backprop Targets »
Maxence ERNOULT · Fabrice Normandin · Abhinav Moudgil · Sean Spinney · Eugene Belilovsky · Irina Rish · Blake Richards · Yoshua Bengio -
2022 Spotlight: Towards Scaling Difference Target Propagation by Learning Backprop Targets »
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2021 : Invited Talk #4 »
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2021 Poster: Spectral Normalisation for Deep Reinforcement Learning: An Optimisation Perspective »
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2021 Spotlight: Spectral Normalisation for Deep Reinforcement Learning: An Optimisation Perspective »
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2020 : Panel Discussion »
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2020 : Q&A with Irina Rish »
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2020 : Invited Talk: Lifelong Learning: Towards Broad and Robust AI by Irina Rish »
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2020 : Invited Talk: Razvan Pascanu "Continual Learning from an Optimization/Learning-dynamics perspective" »
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2020 Workshop: Workshop on Continual Learning »
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2020 Poster: Stabilizing Transformers for Reinforcement Learning »
Emilio Parisotto · Francis Song · Jack Rae · Razvan Pascanu · Caglar Gulcehre · Siddhant Jayakumar · Max Jaderberg · Raphael Lopez Kaufman · Aidan Clark · Seb Noury · Matthew Botvinick · Nicolas Heess · Raia Hadsell -
2020 Poster: Improving the Gating Mechanism of Recurrent Neural Networks »
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2018 Poster: Progress & Compress: A scalable framework for continual learning »
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2018 Poster: Mix & Match - Agent Curricula for Reinforcement Learning »
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2018 Oral: Progress & Compress: A scalable framework for continual learning »
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2018 Oral: Mix & Match - Agent Curricula for Reinforcement Learning »
Wojciech Czarnecki · Siddhant Jayakumar · Max Jaderberg · Leonard Hasenclever · Yee Teh · Nicolas Heess · Simon Osindero · Razvan Pascanu -
2018 Poster: Been There, Done That: Meta-Learning with Episodic Recall »
Samuel Ritter · Jane Wang · Zeb Kurth-Nelson · Siddhant Jayakumar · Charles Blundell · Razvan Pascanu · Matthew Botvinick -
2018 Oral: Been There, Done That: Meta-Learning with Episodic Recall »
Samuel Ritter · Jane Wang · Zeb Kurth-Nelson · Siddhant Jayakumar · Charles Blundell · Razvan Pascanu · Matthew Botvinick -
2017 Poster: Sharp Minima Can Generalize For Deep Nets »
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2017 Talk: Sharp Minima Can Generalize For Deep Nets »
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