Simonyan, Karen

Very Deep Convolutional Networks for Large-Scale Image Recognition

Simonyan, K., & Zisserman, A. (2014) · arXiv

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 114,148

Mastering the game of Go without human knowledge

Silver, D., Schrittwieser, J., Simonyan, K., Antonoglou, I., Huang, A., Guez, A., Hubert, T., Baker, L., Lai, M., Bolton, A., et al. (2017) · Nature

Artificial Intelligence in GamesReinforcement Learning in Robotics

Cited by 9,084

Two-Stream Convolutional Networks for Action Recognition in Videos

Simonyan, K., & Zisserman, A. (2014) · arXiv

Human Pose and Action RecognitionHand Gesture Recognition Systems

Cited by 6,756

Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps

Simonyan, K., Vedaldi, A., & Zisserman, A. (2013) · arXiv

Advanced Neural Network ApplicationsExplainable Artificial Intelligence (XAI)

Cited by 5,370

Spatial transformer networks

Jaderberg, M., Simonyan, K., Zisserman, A., & Kavukcuoglu, K. (2015) · arXiv

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 5,137

WaveNet: a generative model for raw audio

Oord, A. V. D., Dieleman, S., Zen, H., Simonyan, K., Vinyals, O., Graves, A., Kalchbrenner, N., Senior, A., & Kavukcuoglu, K. (2016) · arXiv

Speech Recognition and SynthesisSpeech and Audio Processing

Cited by 4,911

Large Scale GAN Training for High Fidelity Natural Image Synthesis

Brock, A., Donahue, J., & Simonyan, K. (2018) · arXiv

Generative Adversarial Networks and Image SynthesisDigital Media Forensic Detection

Cited by 3,717

A general reinforcement learning algorithm that masters chess, shogi, and Go through self-play

Silver, D., Hubert, T., Schrittwieser, J., Antonoglou, I., Lai, M., Guez, A., Lanctot, M., Sifre, L., Kumaran, D., Graepel, T., et al. (2018) · Science

Artificial Intelligence in GamesReinforcement Learning in Robotics

Cited by 3,562

Improved protein structure prediction using potentials from deep learning

Senior, A. W., Evans, R., Jumper, J., Kirkpatrick, J., Sifre, L., Green, T., Qin, C., Žídek, A., Nelson, A. W. R., Bridgland, A., et al. (2020) · Nature

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 3,378

Return of the Devil in the Details: Delving Deep into Convolutional Nets

Chatfield, K., Simonyan, K., Vedaldi, A., & Zisserman, A. (2014) · Proceedings of the British Machine Vision Conference 2014

Advanced Neural Network ApplicationsAdvanced Image and Video Retrieval Techniques

Cited by 3,335

DARTS: Differentiable architecture search

Liu, H., Simonyan, K., & Yang, Y. (2018) · arXiv

Advanced Neural Network ApplicationsMachine Learning and Data Classification

Cited by 3,248

Flamingo: a Visual Language Model for Few-Shot Learning

Alayrac, J.-B., Donahue, J., Luc, P., Miech, A., Barr, I., Hasson, Y., Lenc, K., Mensch, A., Millican, K., Reynolds, M., et al. (2022) · arXiv

Multimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning

Cited by 1,555

Reading text in the wild with convolutional neural networks

Jaderberg, M., Simonyan, K., Vedaldi, A., & Zisserman, A. (2016) · International Journal of Computer Vision

Handwritten Text Recognition TechniquesVehicle License Plate Recognition

Cited by 1,191

Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm

Silver, D., Hubert, T., Schrittwieser, J., Antonoglou, I., Lai, M., Guez, A., Lanctot, M., Sifre, L., Kumaran, D., Graepel, T., et al. (2017) · arXiv

Artificial Intelligence in GamesReinforcement Learning in Robotics

Cited by 1,102

Skilful precipitation nowcasting using deep generative models of radar

Ravuri, S., Lenc, K., Willson, M., Kangin, D., Lam, R., Mirowski, P., Fitzsimons, M., Athanassiadou, M., Kashem, S., Madge, S., et al. (2021) · Nature

Precipitation Measurement and AnalysisMeteorological Phenomena and Simulations

Cited by 1,024

Training Compute-Optimal Large Language Models

Hoffmann, J., Borgeaud, S., Mensch, A., Buchatskaya, E., Cai, T., Rutherford, E., Casas, D. D. L., Hendricks, L. A., Welbl, J., Clark, A., et al. (2022) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 929

Neural Machine Translation in Linear Time

Kalchbrenner, N., Espeholt, L., Simonyan, K., Oord, A. V. D., Graves, A., & Kavukcuoglu, K. (2016) · arXiv

Natural Language Processing TechniquesTopic Modeling

Cited by 414

Improving language models by retrieving from trillions of tokens

Borgeaud, S., Mensch, A., Hoffmann, J., Cai, T., Rutherford, E., Millican, K., Driessche, G. V. D., Lespiau, J.-B., Damoc, B., Clark, A., et al. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 382

Protein structure prediction using multiple deep neural networks in the 13th critical assessment of protein structure prediction (CASP13)

Senior, A. W., Evans, R., Jumper, J., Kirkpatrick, J., Sifre, L., Green, T., Qin, C., Žídek, A., Nelson, A. W. R., Bridgland, A., et al. (2019) · Proteins: Structure, Function, and Bioinformatics

Protein Structure and DynamicsMachine Learning in Bioinformatics

Cited by 347

Population Based Training of Neural Networks

Jaderberg, M., Dalibard, V., Osindero, S., Czarnecki, W. M., Donahue, J., Razavi, A., Vinyals, O., Green, T., Dunning, I., Simonyan, K., et al. (2017) · arXiv

Machine Learning and Data ClassificationStochastic Gradient Optimization Techniques

Cited by 284

Scaling Language Models: Methods, Analysis & Insights from Training Gopher

Rae, J. W., Borgeaud, S., Cai, T., Millican, K., Hoffmann, J., Song, F., Aslanides, J., Henderson, S., Ring, R., Young, S., et al. (2021) · arXiv

Topic ModelingNatural Language Processing Techniques

Cited by 235

Adversarial Video Generation on Complex Datasets

Clark, A., Donahue, J., & Simonyan, K. (2019) · arXiv

Generative Adversarial Networks and Image SynthesisDigital Media Forensic Detection

Cited by 157

Kickstarting Deep Reinforcement Learning

Schmitt, S., Hudson, J. J., Zidek, A., Osindero, S., Doersch, C., Czarnecki, W. M., Leibo, J. Z., Kuttler, H., Zisserman, A., Simonyan, K., et al. (2018) · arXiv

Reinforcement Learning in RoboticsDomain Adaptation and Few-Shot Learning

Cited by 67

Unified Scaling Laws for Routed Language Models

Clark, A., Casas, D. D. L., Guy, A., Mensch, A., Paganini, M., Hoffmann, J., Damoc, B., Hechtman, B., Cai, T., Borgeaud, S., et al. (2022) · arXiv

Advanced Neural Network ApplicationsTopic Modeling

Cited by 40