Fast video super-resolution via classification. - Karen Simonyan; Sergey Grishin; Dmitriy S. Vatolin; Dmitriy Popov (ICIP, 2008)

Video super-resolution using motion compensation and classification-aided fusion. - Karen Simonyan; Sergey Grishin; Dmitriy S. Vatolin; Dmitriy Popov (SCCG, 2008)

Edge-Directed Interpolation in a Bayesian Framework. - Karen Simonyan; Dmitriy S. Vatolin (BMVC, 2009)

Immediate Structured Visual Search for Medical Images. - Karen Simonyan; Andrew Zisserman; Antonio Criminisi (MICCAI (3), 2011)

Descriptor Learning Using Convex Optimisation. - Karen Simonyan; Andrea Vedaldi; Andrew Zisserman (ECCV (1), 2012)

Immediate ROI Search for 3-D Medical Images. - Karen Simonyan; Marc Modat; Sébastien Ourselin; David M. Cash; Antonio Criminisi; Andrew Zisserman (MCBR-CDS, 2012)

Fisher Vector Faces in the Wild. - Karen Simonyan; Omkar M. Parkhi; Andrea Vedaldi; Andrew Zisserman (BMVC, 2013)

Deep Fisher Networks for Large-Scale Image Classification. - Karen Simonyan; Andrea Vedaldi; Andrew Zisserman (NIPS, 2013)

Large-scale learning of discriminative image representations. - Karen Simonyan (2013)

Efficient On-the-fly Category Retrieval Using ConvNets and GPUs. - Ken Chatfield; Karen Simonyan; Andrew Zisserman (ACCV (1), 2014)

Deep Convolutional Neural Networks for Efficient Pose Estimation in Gesture Videos. - Tomas Pfister; Karen Simonyan; James Charles; Andrew Zisserman (ACCV (1), 2014)

Return of the Devil in the Details: Delving Deep into Convolutional Nets. - Ken Chatfield; Karen Simonyan; Andrea Vedaldi; Andrew Zisserman (BMVC, 2014)

A Compact and Discriminative Face Track Descriptor. - Omkar M. Parkhi; Karen Simonyan; Andrea Vedaldi; Andrew Zisserman (CVPR, 2014)

Understanding Objects in Detail with Fine-Grained Attributes. - Andrea Vedaldi; Siddharth Mahendran; Stavros Tsogkas; Subhransu Maji; Ross B. Girshick; Juho Kannala; Esa Rahtu; Iasonas Kokkinos; Matthew B. Blaschko; David J. Weiss; Ben Taskar; Karen Simonyan; et al. (CVPR, 2014)

Two-Stream Convolutional Networks for Action Recognition in Videos. - Karen Simonyan; Andrew Zisserman (NIPS, 2014)

Synthetic Data and Artificial Neural Networks for Natural Scene Text Recognition. - Max Jaderberg; Karen Simonyan; Andrea Vedaldi; Andrew Zisserman (CoRR, 2014)

Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps. - Karen Simonyan; Andrea Vedaldi; Andrew Zisserman (ICLR (Workshop Poster), 2014)

Learning Local Feature Descriptors Using Convex Optimisation. - Karen Simonyan; Andrea Vedaldi; Andrew Zisserman (IEEE Trans. Pattern Anal. Mach. Intell., 2014)

Natural Neural Networks. - Guillaume Desjardins; Karen Simonyan; Razvan Pascanu; Koray Kavukcuoglu (NIPS, 2015)

Spatial Transformer Networks. - Max Jaderberg; Karen Simonyan; Andrew Zisserman; Koray Kavukcuoglu (NIPS, 2015)

Deep Structured Output Learning for Unconstrained Text Recognition. - Max Jaderberg; Karen Simonyan; Andrea Vedaldi; Andrew Zisserman (ICLR, 2015)

Very Deep Convolutional Networks for Large-Scale Image Recognition. - Karen Simonyan; Andrew Zisserman (ICLR, 2015)

WaveNet: A Generative Model for Raw Audio. - Aäron van den Oord; Sander Dieleman; Heiga Zen; Karen Simonyan; Oriol Vinyals; Alex Graves; Nal Kalchbrenner; Andrew W. Senior; Koray Kavukcuoglu (SSW, 2016)

Neural Machine Translation in Linear Time. - Nal Kalchbrenner; Lasse Espeholt; Karen Simonyan; Aäron van den Oord; Alex Graves; Koray Kavukcuoglu (CoRR, 2016)

Reading Text in the Wild with Convolutional Neural Networks. - Max Jaderberg; Karen Simonyan; Andrea Vedaldi; Andrew Zisserman (Int. J. Comput. Vis., 2016)

Neural Audio Synthesis of Musical Notes with WaveNet Autoencoders. - Jesse H. Engel; Cinjon Resnick; Adam Roberts; Sander Dieleman; Mohammad Norouzi 002; Douglas Eck; Karen Simonyan (ICML, 2017)

Video Pixel Networks. - Nal Kalchbrenner; Aäron van den Oord; Karen Simonyan; Ivo Danihelka; Oriol Vinyals; Alex Graves; Koray Kavukcuoglu (ICML, 2017)

The Kinetics Human Action Video Dataset. - Will Kay; João Carreira 001; Karen Simonyan; Brian Zhang; Chloe Hillier; Sudheendra Vijayanarasimhan; Fabio Viola; Tim Green; Trevor Back; Paul Natsev; Mustafa Suleyman; Andrew Zisserman (CoRR, 2017)

StarCraft II: A New Challenge for Reinforcement Learning. - Oriol Vinyals; Timo Ewalds; Sergey Bartunov; Petko Georgiev; Alexander Sasha Vezhnevets; Michelle Yeo; Alireza Makhzani; Heinrich Küttler; John P. Agapiou; Julian Schrittwieser; John Quan; Stephen Gaffney; et al. (CoRR, 2017)

Population Based Training of Neural Networks. - Max Jaderberg; Valentin Dalibard; Simon Osindero; Wojciech M. Czarnecki; Jeff Donahue; Ali Razavi; Oriol Vinyals; Tim Green; Iain Dunning; Karen Simonyan; Chrisantha Fernando; Koray Kavukcuoglu (CoRR, 2017)

Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm. - David Silver; Thomas Hubert; Julian Schrittwieser; Ioannis Antonoglou; Matthew Lai; Arthur Guez; Marc Lanctot; Laurent Sifre; Dharshan Kumaran; Thore Graepel; Timothy P. Lillicrap; Karen Simonyan; et al. (CoRR, 2017)

Mastering the game of Go without human knowledge. - David Silver; Julian Schrittwieser; Karen Simonyan; Ioannis Antonoglou; Aja Huang; Arthur Guez; Thomas Hubert; Lucas Baker; Matthew Lai; Adrian Bolton; Yutian Chen 001; Timothy P. Lillicrap; et al. (Nat., 2017)

Hierarchical Representations for Efficient Architecture Search. - Hanxiao Liu; Karen Simonyan; Oriol Vinyals; Chrisantha Fernando; Koray Kavukcuoglu (ICLR (Poster), 2018)

IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures. - Lasse Espeholt; Hubert Soyer; Rémi Munos; Karen Simonyan; Volodymyr Mnih; Tom Ward; Yotam Doron; Vlad Firoiu; Tim Harley; Iain Dunning; Shane Legg; Koray Kavukcuoglu (ICML, 2018)

Learning to Search with MCTSnets. - Arthur Guez; Theophane Weber; Ioannis Antonoglou; Karen Simonyan; Oriol Vinyals; Daan Wierstra; Rémi Munos; David Silver (ICML, 2018)

Efficient Neural Audio Synthesis. - Nal Kalchbrenner; Erich Elsen; Karen Simonyan; Seb Noury; Norman Casagrande; Edward Lockhart; Florian Stimberg; Aäron van den Oord; Sander Dieleman; Koray Kavukcuoglu (ICML, 2018)

Parallel WaveNet: Fast High-Fidelity Speech Synthesis. - Aäron van den Oord; Yazhe Li; Igor Babuschkin; Karen Simonyan; Oriol Vinyals; Koray Kavukcuoglu; George van den Driessche 002; Edward Lockhart; Luis C. Cobo; Florian Stimberg; Norman Casagrande; Dominik Grewe; et al. (ICML, 2018)

The challenge of realistic music generation: modelling raw audio at scale. - Sander Dieleman; Aäron van den Oord; Karen Simonyan (NeurIPS, 2018)

Learning to Navigate in Cities Without a Map. - Piotr Mirowski; Matthew Koichi Grimes; Mateusz Malinowski; Karl Moritz Hermann; Keith Anderson; Denis Teplyashin; Karen Simonyan; Koray Kavukcuoglu; Andrew Zisserman; Raia Hadsell (NeurIPS, 2018)

Kickstarting Deep Reinforcement Learning. - Simon Schmitt; Jonathan J. Hudson; Augustin Zídek; Simon Osindero; Carl Doersch; Wojciech M. Czarnecki; Joel Z. Leibo; Heinrich Küttler; Andrew Zisserman; Karen Simonyan; S. M. Ali Eslami (CoRR, 2018)

Large Scale GAN Training for High Fidelity Natural Image Synthesis. - Andrew Brock; Jeff Donahue; Karen Simonyan (ICLR, 2019)

DARTS: Differentiable Architecture Search. - Hanxiao Liu; Karen Simonyan; Yiming Yang (ICLR (Poster), 2019)

Large Scale Adversarial Representation Learning. - Jeff Donahue; Karen Simonyan (NeurIPS, 2019)

The StreetLearn Environment and Dataset. - Piotr Mirowski; Andras Banki-Horvath; Keith Anderson; Denis Teplyashin; Karl Moritz Hermann; Mateusz Malinowski; Matthew Koichi Grimes; Karen Simonyan; Koray Kavukcuoglu; Andrew Zisserman; Raia Hadsell (CoRR, 2019)

Hierarchical Autoregressive Image Models with Auxiliary Decoders. - Jeffrey De Fauw; Sander Dieleman; Karen Simonyan (CoRR, 2019)

Non-Differentiable Supervised Learning with Evolution Strategies and Hybrid Methods. - Karel Lenc; Erich Elsen; Tom Schaul; Karen Simonyan (CoRR, 2019)

Efficient Video Generation on Complex Datasets. - Aidan Clark; Jeff Donahue; Karen Simonyan (CoRR, 2019)

LOGAN: Latent Optimisation for Generative Adversarial Networks. - Yan Wu 010; Jeff Donahue; David Balduzzi; Karen Simonyan; Timothy P. Lillicrap (CoRR, 2019)

Fast Sparse ConvNets. - Erich Elsen; Marat Dukhan; Trevor Gale; Karen Simonyan (CVPR, 2020)

High Fidelity Speech Synthesis with Adversarial Networks. - Mikolaj Binkowski; Jeff Donahue; Sander Dieleman; Aidan Clark; Erich Elsen; Norman Casagrande; Luis C. Cobo; Karen Simonyan (ICLR, 2020)

Off-Policy Actor-Critic with Shared Experience Replay. - Simon Schmitt; Matteo Hessel; Karen Simonyan (ICML, 2020)

Evolving Normalization-Activation Layers. - Hanxiao Liu; Andy Brock; Karen Simonyan; Quoc Le 001 (NeurIPS, 2020)

Transformation-based Adversarial Video Prediction on Large-Scale Data. - Pauline Luc; Aidan Clark; Sander Dieleman; Diego de Las Casas; Yotam Doron; Albin Cassirer; Karen Simonyan (CoRR, 2020)

A Practical Sparse Approximation for Real Time Recurrent Learning. - Jacob Menick; Erich Elsen; Utku Evci; Simon Osindero; Karen Simonyan; Alex Graves (CoRR, 2020)

AlgebraNets. - Jordan Hoffmann; Simon Schmitt; Simon Osindero; Karen Simonyan; Erich Elsen (CoRR, 2020)

Mastering Atari, Go, chess and shogi by planning with a learned model. - Julian Schrittwieser; Ioannis Antonoglou; Thomas Hubert; Karen Simonyan; Laurent Sifre; Simon Schmitt; Arthur Guez; Edward Lockhart; Demis Hassabis; Thore Graepel; Timothy P. Lillicrap; David Silver (Nat., 2020)

Improved protein structure prediction using potentials from deep learning. - Andrew W. Senior; Richard Evans 001; John Jumper; James Kirkpatrick; Laurent Sifre; Tim Green; Chongli Qin; Augustin Zídek; Alexander W. R. Nelson; Alex Bridgland; Hugo Penedones; Stig Petersen; et al. (Nat., 2020)

This time with feeling: learning expressive musical performance. - Sageev Oore; Ian Simon; Sander Dieleman; Douglas Eck; Karen Simonyan (Neural Comput. Appl., 2020)

Machine Translation Decoding beyond Beam Search. - Rémi Leblond; Jean-Baptiste Alayrac; Laurent Sifre; Miruna Pislar; Jean-Baptiste Lespiau; Ioannis Antonoglou; Karen Simonyan; Oriol Vinyals (EMNLP (1), 2021)

End-to-end Adversarial Text-to-Speech. - Jeff Donahue; Sander Dieleman; Mikolaj Binkowski; Erich Elsen; Karen Simonyan (ICLR, 2021)

Practical Real Time Recurrent Learning with a Sparse Approximation. - Jacob Menick; Erich Elsen; Utku Evci; Simon Osindero; Karen Simonyan; Alex Graves (ICLR, 2021)

High-Performance Large-Scale Image Recognition Without Normalization. - Andy Brock; Soham De; Samuel L. Smith; Karen Simonyan (ICML, 2021)

Variable-rate discrete representation learning. - Sander Dieleman; Charlie Nash; Jesse H. Engel; Karen Simonyan (CoRR, 2021)

Skillful Precipitation Nowcasting using Deep Generative Models of Radar. - Suman V. Ravuri; Karel Lenc; Matthew Willson; Dmitry Kangin; Rémi Lam; Piotr Mirowski; Megan Fitzsimons; Maria Athanassiadou; Sheleem Kashem; Sam Madge; Rachel Prudden; Amol Mandhane; et al. (CoRR, 2021)

Scaling Language Models: Methods, Analysis & Insights from Training Gopher. - 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; et al. (CoRR, 2021)

Skilful precipitation nowcasting using deep generative models of radar. - Suman V. Ravuri; Karel Lenc; Matthew Willson; Dmitry Kangin; Rémi Lam; Piotr Mirowski; Megan Fitzsimons; Maria Athanassiadou; Sheleem Kashem; Sam Madge; Rachel Prudden; Amol Mandhane; et al. (Nat., 2021)

Improving Language Models by Retrieving from Trillions of Tokens. - Sebastian Borgeaud; Arthur Mensch; Jordan Hoffmann; Trevor Cai; Eliza Rutherford; Katie Millican; George van den Driessche 002; Jean-Baptiste Lespiau; Bogdan Damoc; Aidan Clark; Diego de Las Casas; Aurelia Guy; et al. (ICML, 2022)

Unified Scaling Laws for Routed Language Models. - Aidan Clark; Diego de Las Casas; Aurelia Guy; Arthur Mensch; Michela Paganini; Jordan Hoffmann; Bogdan Damoc; Blake A. Hechtman; Trevor Cai; Sebastian Borgeaud; George van den Driessche 002; Eliza Rutherford; et al. (ICML, 2022)

Flamingo: a Visual Language Model for Few-Shot Learning. - Jean-Baptiste Alayrac; Jeff Donahue; Pauline Luc; Antoine Miech; Iain Barr; Yana Hasson; Karel Lenc; Arthur Mensch; Katherine Millican; Malcolm Reynolds; Roman Ring; Eliza Rutherford; et al. (NeurIPS, 2022)

An empirical analysis of compute-optimal large language model training. - Jordan Hoffmann; Sebastian Borgeaud; Arthur Mensch; Elena Buchatskaya; Trevor Cai; Eliza Rutherford; Diego de Las Casas; Lisa Anne Hendricks; Johannes Welbl; Aidan Clark; Tom Hennigan; Eric Noland; et al. (NeurIPS, 2022)

Unified Scaling Laws for Routed Language Models. - Aidan Clark; Diego de Las Casas; Aurelia Guy; Arthur Mensch; Michela Paganini; Jordan Hoffmann; Bogdan Damoc; Blake A. Hechtman; Trevor Cai; Sebastian Borgeaud; George van den Driessche 002; Eliza Rutherford; et al. (CoRR, 2022)

Hierarchical Perceiver. - João Carreira 001; Skanda Koppula; Daniel Zoran; Adrià Recasens; Catalin Ionescu; Olivier J. Hénaff; Evan Shelhamer; Relja Arandjelovic; Matthew M. Botvinick; Oriol Vinyals; Karen Simonyan; Andrew Zisserman; et al. (CoRR, 2022)

Training Compute-Optimal Large Language Models. - Jordan Hoffmann; Sebastian Borgeaud; Arthur Mensch; Elena Buchatskaya; Trevor Cai; Eliza Rutherford; Diego de Las Casas; Lisa Anne Hendricks; Johannes Welbl; Aidan Clark; Tom Hennigan; Eric Noland; et al. (CoRR, 2022)

Flamingo: a Visual Language Model for Few-Shot Learning. - Jean-Baptiste Alayrac; Jeff Donahue; Pauline Luc; Antoine Miech; Iain Barr; Yana Hasson; Karel Lenc; Arthur Mensch; Katie Millican; Malcolm Reynolds; Roman Ring; Eliza Rutherford; et al. (CoRR, 2022)