• case-insensitive prefix search: default
  e.g., sig matches "SIGIR" as well as "signal"
• exact word search: append dollar sign ($) to word
  e.g., graph$ matches "graph", but not "graphics"
• boolean and: separate words by space
  e.g., codd model
• boolean or: connect words by pipe symbol (|)
  e.g., graph|network

Update May 7, 2017: Please note that we had to disable the phrase search operator (.) and the boolean not operator (-) due to technical problems. For the time being, phrase search queries will yield regular prefix search result, and search terms preceded by a minus will be interpreted as regular (positive) search terms.

found 61 matches

• 2024
• 
  Clare Lyle, Zeyu Zheng, Khimya Khetarpal, Hado van Hasselt, Razvan Pascanu, James Martens, Will Dabney:
  Disentangling the Causes of Plasticity Loss in Neural Networks. CoRR abs/2402.18762 (2024)
• 
  James Hinns, David Martens:
  Exposing Image Classifier Shortcuts with Counterfactual Frequency (CoF) Tables. CoRR abs/2405.15661 (2024)
• 
  Clare Lyle, Zeyu Zheng, Khimya Khetarpal, James Martens, Hado van Hasselt, Razvan Pascanu, Will Dabney:
  Normalization and effective learning rates in reinforcement learning. CoRR abs/2407.01800 (2024)
• 2023
• 
  Bobby He, James Martens, Guodong Zhang, Aleksandar Botev, Andrew Brock, Samuel L. Smith, Yee Whye Teh:
  Deep Transformers without Shortcuts: Modifying Self-attention for Faithful Signal Propagation. ICLR 2023
• 
  Sheheryar Zaidi, Michael Schaarschmidt, James Martens, Hyunjik Kim, Yee Whye Teh, Alvaro Sanchez-Gonzalez, Peter W. Battaglia, Razvan Pascanu, Jonathan Godwin:
  Pre-training via Denoising for Molecular Property Prediction. ICLR 2023
• 
  Bobby He, James Martens, Guodong Zhang, Aleksandar Botev, Andrew Brock, Samuel L. Smith, Yee Whye Teh:
  Deep Transformers without Shortcuts: Modifying Self-attention for Faithful Signal Propagation. CoRR abs/2302.10322 (2023)
• 
  David Martens, Camille Dams, James Hinns, Mark Vergouwen:
  Tell Me a Story! Narrative-Driven XAI with Large Language Models. CoRR abs/2309.17057 (2023)
• 2022
• 
  Pieter Verschaffelt, James H. Collier, Alexander Botzki, Lennart Martens, Peter Dawyndt, Bart Mesuere:
  Unipept Visualizations: an interactive visualization library for biological data. Bioinform. 38(2): 562-563 (2022)
• 
  Guodong Zhang, Aleksandar Botev, James Martens:
  Deep Learning without Shortcuts: Shaping the Kernel with Tailored Rectifiers. ICLR 2022
• 
  Guodong Zhang, Aleksandar Botev, James Martens:
  Deep Learning without Shortcuts: Shaping the Kernel with Tailored Rectifiers. CoRR abs/2203.08120 (2022)
• 
  Sheheryar Zaidi, Michael Schaarschmidt, James Martens, Hyunjik Kim, Yee Whye Teh, Alvaro Sanchez-Gonzalez, Peter W. Battaglia, Razvan Pascanu, Jonathan Godwin:
  Pre-training via Denoising for Molecular Property Prediction. CoRR abs/2206.00133 (2022)
• 2021
• 
  Wengran Wang, Archit Kwatra, James Skripchuk, Neeloy Gomes, Alexandra Milliken, Chris Martens, Tiffany Barnes, Thomas W. Price:
  Novices' Learning Barriers When Using Code Examples in Open-Ended Programming. ITiCSE (1) 2021: 394-400
• 
  Friedrich-Maximilian Jaenichen, Christina Johanna Liepold, Abdelgafar Ismail, Christian James Martens, Volker Dörrsam, Hans Ehm:
  Simulating and Evaluating Supply Chain Disruptions Along an End-to-End Semiconductor Automotive Supply Chain. WSC 2021: 1-12
• 
  James Martens:
  On the validity of kernel approximations for orthogonally-initialized neural networks. CoRR abs/2104.05878 (2021)
• 
  Wengran Wang, Archit Kwatra, James Skripchuk, Neeloy Gomes, Alexandra Milliken, Chris Martens, Tiffany Barnes, Thomas W. Price:
  Novices' Learning Barriers When Using Code Examples in Open-Ended Programming. CoRR abs/2104.11806 (2021)
• 
  James Martens, Andy Ballard, Guillaume Desjardins, Grzegorz Swirszcz, Valentin Dalibard, Jascha Sohl-Dickstein, Samuel S. Schoenholz:
  Rapid training of deep neural networks without skip connections or normalization layers using Deep Kernel Shaping. CoRR abs/2110.01765 (2021)
• 
  Jack W. Rae, Sebastian Borgeaud, Trevor Cai, Katie Millican, Jordan Hoffmann, H. Francis Song, John Aslanides, Sarah Henderson, Roman Ring, Susannah Young, Eliza Rutherford, Tom Hennigan, Jacob Menick, Albin Cassirer, Richard Powell, George van den Driessche, Lisa Anne Hendricks, Maribeth Rauh, Po-Sen Huang, Amelia Glaese, Johannes Welbl, Sumanth Dathathri, Saffron Huang, Jonathan Uesato, John Mellor, Irina Higgins, Antonia Creswell, Nat McAleese, Amy Wu, Erich Elsen, Siddhant M. Jayakumar, Elena Buchatskaya, David Budden, Esme Sutherland, Karen Simonyan, Michela Paganini, Laurent Sifre, Lena Martens, Xiang Lorraine Li, Adhiguna Kuncoro, Aida Nematzadeh, Elena Gribovskaya, Domenic Donato, Angeliki Lazaridou, Arthur Mensch, Jean-Baptiste Lespiau, Maria Tsimpoukelli, Nikolai Grigorev, Doug Fritz, Thibault Sottiaux, Mantas Pajarskas, Toby Pohlen, Zhitao Gong, Daniel Toyama, Cyprien de Masson d'Autume, Yujia Li, Tayfun Terzi, Vladimir Mikulik, Igor Babuschkin, Aidan Clark, Diego de Las Casas, Aurelia Guy, Chris Jones, James Bradbury, Matthew J. Johnson, Blake A. Hechtman, Laura Weidinger, Iason Gabriel, William Isaac, Edward Lockhart, Simon Osindero, Laura Rimell, Chris Dyer, Oriol Vinyals, Kareem Ayoub, Jeff Stanway, Lorrayne Bennett, Demis Hassabis, Koray Kavukcuoglu, Geoffrey Irving:
  Scaling Language Models: Methods, Analysis & Insights from Training Gopher. CoRR abs/2112.11446 (2021)
• 2020
• 
  James Martens:
  New Insights and Perspectives on the Natural Gradient Method. J. Mach. Learn. Res. 21: 146:1-146:76 (2020)
• 
  Rahma Mukta, James Martens, Hye-Young Paik, Qinghua Lu, Salil S. Kanhere:
  Blockchain-based Verifiable Credential Sharing with Selective Disclosure. TrustCom 2020: 959-966
• 
  Nour Ramzy, Christian James Martens, Shreya Singh, Thomas Ponsignon, Hans Ehm:
  First Steps Towards Bridging Simulation and Ontology to Ease the Model Creation on the Example of Semiconductor Industry. WSC 2020: 1789-1800
• 2019
• 
  Alistair Letcher, David Balduzzi, Sébastien Racanière, James Martens, Jakob N. Foerster, Karl Tuyls, Thore Graepel:
  Differentiable Game Mechanics. J. Mach. Learn. Res. 20: 84:1-84:40 (2019)
• 
  Adam Summerville, Chris Martens, Sarah Harmon, Michael Mateas, Joseph C. Osborn, Noah Wardrip-Fruin, Arnav Jhala:
  From Mechanics to Meaning. IEEE Trans. Games 11(1): 69-78 (2019)
• 
  Chongli Qin, James Martens, Sven Gowal, Dilip Krishnan, Krishnamurthy Dvijotham, Alhussein Fawzi, Soham De, Robert Stanforth, Pushmeet Kohli:
  Adversarial Robustness through Local Linearization. NeurIPS 2019: 13824-13833
• 
  Guodong Zhang, Lala Li, Zachary Nado, James Martens, Sushant Sachdeva, George E. Dahl, Christopher J. Shallue, Roger B. Grosse:
  Which Algorithmic Choices Matter at Which Batch Sizes? Insights From a Noisy Quadratic Model. NeurIPS 2019: 8194-8205
• 
  Guodong Zhang, James Martens, Roger B. Grosse:
  Fast Convergence of Natural Gradient Descent for Over-Parameterized Neural Networks. NeurIPS 2019: 8080-8091
• 
  Hans Ehm, Cédric Neau, Christian James Martens, Tim Lauer, Thomas Ponsignon, Joaquin Garcia:
  Research Opportunities Regarding Tree and Network Productstructure Representations in a Semiconductor Supply Chain. WSC 2019: 2429-2440
• 
  Tim Cooijmans, James Martens:
  On the Variance of Unbiased Online Recurrent Optimization. CoRR abs/1902.02405 (2019)
• 
  Alistair Letcher, David Balduzzi, Sébastien Racanière, James Martens, Jakob N. Foerster, Karl Tuyls, Thore Graepel:
  Differentiable Game Mechanics. CoRR abs/1905.04926 (2019)
• 
  Guodong Zhang, James Martens, Roger B. Grosse:
  Fast Convergence of Natural Gradient Descent for Overparameterized Neural Networks. CoRR abs/1905.10961 (2019)
• 
  Chongli Qin, James Martens, Sven Gowal, Dilip Krishnan, Krishnamurthy Dvijotham, Alhussein Fawzi, Soham De, Robert Stanforth, Pushmeet Kohli:
  Adversarial Robustness through Local Linearization. CoRR abs/1907.02610 (2019)

skipping 31 more matches