A fast-match approach for robust, faster than real-time speaker diarization. - Yan Huang; Oriol Vinyals; Gerald Friedland; Christian A. Müller; Nikki Mirghafori; Chuck Wooters (ASRU, 2007)

Learning Kernel Expansions for Image Classification. - Fernando De la Torre; Oriol Vinyals (CVPR, 2007)

Parameterized kernels for support vector machine classification. - Fernando De la Torre; Oriol Vinyals (VISAPP (2), 2007)

Overlapped speech detection for improved speaker diarization in multiparty meetings. - Kofi Boakye; B. Trueba-Hornero; Oriol Vinyals; Gerald Friedland (ICASSP, 2008)

Two's a crowd: improving speaker diarization by automatically identifying and excluding overlapped speech. - Kofi Boakye; Oriol Vinyals; Gerald Friedland (INTERSPEECH, 2008)

Modulation spectrogram features for improved speaker diarization. - Oriol Vinyals; Gerald Friedland (INTERSPEECH, 2008)

A Hardware-Independent Fast Logarithm Approximation with Adjustable Accuracy. - Oriol Vinyals; Gerald Friedland (ISM, 2008)

Live speaker identification in conversations. - Gerald Friedland; Oriol Vinyals (ACM Multimedia, 2008)

Towards Semantic Analysis of Conversations: A System for the Live Identification of Speakers in Meetings. - Oriol Vinyals; Gerald Friedland (ICSC, 2008)

Fusing short term and long term features for improved speaker diarization. - Gerald Friedland; Oriol Vinyals; Yan Huang; Christian A. Müller (ICASSP, 2009)

Discriminative pronounciation learning using phonetic decoder and minimum-classification-error criterion. - Oriol Vinyals; Li Deng 001; Dong Yu 001; Alex Acero (ICASSP, 2009)

Prosodic and other Long-Term Features for Speaker Diarization. - Gerald Friedland; Oriol Vinyals; Yan Huang; Christian A. Müller (IEEE Trans. Speech Audio Process., 2009)

System output combination for improved speaker diarization. - Simon Bozonnet; Nicholas W. D. Evans; Xavier Anguera; Oriol Vinyals; Gerald Friedland; Corinne Fredouille (INTERSPEECH, 2010)

A hybrid approach to online speaker diarization. - Carlos Vaquero; Oriol Vinyals; Gerald Friedland (INTERSPEECH, 2010)

Discriminative training for hierarchical clustering in speaker diarization. - Oriol Vinyals; Gerald Friedland; Nelson Morgan (INTERSPEECH, 2010)

Multimodal location estimation. - Gerald Friedland; Oriol Vinyals; Trevor Darrell (ACM Multimedia, 2010)

Precise indoor localization using smart phones. - Eladio Martin; Oriol Vinyals; Gerald Friedland; Ruzena Bajcsy (ACM Multimedia, 2010)

Multimodal Indoor Localization: An Audio-Wireless-Based Approach. - Oriol Vinyals; Eladio Martin; Gerald Friedland (ICSC, 2010)

Comparing multilayer perceptron to Deep Belief Network Tandem features for robust ASR. - Oriol Vinyals; Suman V. Ravuri (ICASSP, 2011)

Improved Overlapped Speech Handling for Speaker Diarization. - Kofi Boakye; Oriol Vinyals; Gerald Friedland (INTERSPEECH, 2011)

Revisiting Recurrent Neural Networks for robust ASR. - Oriol Vinyals; Suman V. Ravuri; Daniel Povey (ICASSP, 2012)

Learning speaker, addressee and overlap detection models from multimodal streams. - Oriol Vinyals; Dan Bohus; Rich Caruana (ICMI, 2012)

Feature learning using Generalized Extreme Value distribution based K-means clustering. - Zeyu Li 002; Oriol Vinyals; Harlyn Baker; Ruzena Bajcsy (ICPR, 2012)

Recurrent Neural Networks for Noise Reduction in Robust ASR. - Andrew L. Maas; Quoc V. Le; Tyler M. O'Neil; Oriol Vinyals; Patrick Nguyen; Andrew Y. Ng (INTERSPEECH, 2012)

Are Sparse Representations Rich Enough for Acoustic Modeling? - Oriol Vinyals; Li Deng 001 (INTERSPEECH, 2012)

Learning with Recursive Perceptual Representations. - Oriol Vinyals; Yangqing Jia; Li Deng 001; Trevor Darrell (NIPS, 2012)

Krylov Subspace Descent for Deep Learning. - Oriol Vinyals; Daniel Povey (AISTATS, 2012)

The ICSI RT-09 Speaker Diarization System. - Gerald Friedland; Adam Janin; David Imseng; Xavier Anguera Miró; Luke R. Gottlieb; Marijn Huijbregts; Mary Tai Knox; Oriol Vinyals (IEEE Trans. Speech Audio Process., 2012)

Speaker Diarization: A Review of Recent Research. - Xavier Anguera Miró; Simon Bozonnet; Nicholas W. D. Evans; Corinne Fredouille; Gerald Friedland; Oriol Vinyals (IEEE Trans. Speech Audio Process., 2012)

On Compact Codes for Spatially Pooled Features. - Yangqing Jia; Oriol Vinyals; Trevor Darrell (ICML (3), 2013)

Deep vs. wide: depth on a budget for robust speech recognition. - Oriol Vinyals; Nelson Morgan (INTERSPEECH, 2013)

Why Size Matters: Feature Coding as Nystrom Sampling - Oriol Vinyals; Yangqing Jia; Trevor Darrell (ICLR (Workshop), 2013)

Pooling-Invariant Image Feature Learning - Yangqing Jia; Oriol Vinyals; Trevor Darrell (CoRR, 2013)

Beyond Deep Learning: Scalable Methods and Models for Learning. - Oriol Vinyals (2013)

Chasing the metric: Smoothing learning algorithms for keyword detection. - Oriol Vinyals; Steven Wegmann (ICASSP, 2014)

DeCAF: A Deep Convolutional Activation Feature for Generic Visual Recognition. - Jeff Donahue; Yangqing Jia; Oriol Vinyals; Judy Hoffman; Ning Zhang 014; Eric Tzeng; Trevor Darrell (ICML, 2014)

Sequence discriminative distributed training of long short-term memory recurrent neural networks. - Hasim Sak; Oriol Vinyals; Georg Heigold; Andrew W. Senior; Erik McDermott; Rajat Monga; Mark Z. Mao (INTERSPEECH, 2014)

Sequence to Sequence Learning with Neural Networks. - Ilya Sutskever; Oriol Vinyals; Quoc V. Le (NIPS, 2014)

Recurrent Neural Network Regularization. - Wojciech Zaremba; Ilya Sutskever; Oriol Vinyals (CoRR, 2014)

Addressing the Rare Word Problem in Neural Machine Translation. - Thang Luong; Ilya Sutskever; Quoc V. Le; Oriol Vinyals; Wojciech Zaremba (ACL (1), 2015)

Beyond short snippets: Deep networks for video classification. - Joe Yue-Hei Ng; Matthew J. Hausknecht; Sudheendra Vijayanarasimhan; Oriol Vinyals; Rajat Monga; George Toderici (CVPR, 2015)

Show and tell: A neural image caption generator. - Oriol Vinyals; Alexander Toshev; Samy Bengio; Dumitru Erhan (CVPR, 2015)

Sentence Compression by Deletion with LSTMs. - Katja Filippova; Enrique Alfonseca; Carlos A. Colmenares; Lukasz Kaiser; Oriol Vinyals (EMNLP, 2015)

Convolutional, Long Short-Term Memory, fully connected Deep Neural Networks. - Tara N. Sainath; Oriol Vinyals; Andrew W. Senior; Hasim Sak (ICASSP, 2015)

Learning the speech front-end with raw waveform CLDNNs. - Tara N. Sainath; Ron J. Weiss; Andrew W. Senior; Kevin W. Wilson; Oriol Vinyals (INTERSPEECH, 2015)

Scheduled Sampling for Sequence Prediction with Recurrent Neural Networks. - Samy Bengio; Oriol Vinyals; Navdeep Jaitly; Noam Shazeer (NIPS, 2015)

Pointer Networks. - Oriol Vinyals; Meire Fortunato; Navdeep Jaitly (NIPS, 2015)

Grammar as a Foreign Language. - Oriol Vinyals; Lukasz Kaiser; Terry Koo; Slav Petrov; Ilya Sutskever; Geoffrey E. Hinton (NIPS, 2015)

Listen, Attend and Spell. - William Chan; Navdeep Jaitly; Quoc V. Le; Oriol Vinyals (CoRR, 2015)

Qualitatively characterizing neural network optimization problems. - Ian J. Goodfellow; Oriol Vinyals (ICLR, 2015)

Distilling the Knowledge in a Neural Network. - Geoffrey E. Hinton; Oriol Vinyals; Jeffrey Dean (CoRR, 2015)

An Online Sequence-to-Sequence Model Using Partial Conditioning. - Navdeep Jaitly; Quoc V. Le; Oriol Vinyals; Ilya Sutskever; Samy Bengio (CoRR, 2015)

Towards Principled Unsupervised Learning. - Ilya Sutskever; Rafal Józefowicz; Karol Gregor; Danilo Jimenez Rezende; Timothy P. Lillicrap; Oriol Vinyals (CoRR, 2015)

A Neural Conversational Model. - Oriol Vinyals; Quoc V. Le (CoRR, 2015)

Generating Sentences from a Continuous Space. - Samuel R. Bowman; Luke Vilnis; Oriol Vinyals; Andrew M. Dai; Rafal Józefowicz; Samy Bengio (CoNLL, 2016)

Listen, attend and spell: A neural network for large vocabulary conversational speech recognition. - William Chan; Navdeep Jaitly; Quoc V. Le; Oriol Vinyals (ICASSP, 2016)

Multilingual Language Processing From Bytes. - Dan Gillick; Cliff Brunk; Oriol Vinyals; Amarnag Subramanya (HLT-NAACL, 2016)

An Online Sequence-to-Sequence Model Using Partial Conditioning. - Navdeep Jaitly; Quoc V. Le; Oriol Vinyals; Ilya Sutskever; David Sussillo; Samy Bengio (NIPS, 2016)

Conditional Image Generation with PixelCNN Decoders. - Aäron van den Oord; Nal Kalchbrenner; Lasse Espeholt; Koray Kavukcuoglu; Oriol Vinyals; Alex Graves (NIPS, 2016)

Strategic Attentive Writer for Learning Macro-Actions. - Alexander Vezhnevets; Volodymyr Mnih; Simon Osindero; Alex Graves; Oriol Vinyals; John P. Agapiou; Koray Kavukcuoglu (NIPS, 2016)

Matching Networks for One Shot Learning. - Oriol Vinyals; Charles Blundell; Tim Lillicrap; Koray Kavukcuoglu; Daan Wierstra (NIPS, 2016)

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)

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems. - Martín Abadi; Ashish Agarwal; Paul Barham 001; Eugene Brevdo; Zhifeng Chen; Craig Citro; Gregory S. Corrado; Andy Davis; Jeffrey Dean; Matthieu Devin; Sanjay Ghemawat; Ian J. Goodfellow; et al. (CoRR, 2016)

Contextual LSTM (CLSTM) models for Large scale NLP tasks. - Shalini Ghosh; Oriol Vinyals; Brian Strope; Scott Roy; Tom Dean; Larry P. Heck (CoRR, 2016)

Decoupled Neural Interfaces using Synthetic Gradients. - Max Jaderberg; Wojciech Marian Czarnecki; Simon Osindero; Oriol Vinyals; Alex Graves; Koray Kavukcuoglu (CoRR, 2016)

Exploring the Limits of Language Modeling. - Rafal Józefowicz; Oriol Vinyals; Mike Schuster; Noam Shazeer; Yonghui Wu (CoRR, 2016)

Multi-task Sequence to Sequence Learning. - Minh-Thang Luong; Quoc V. Le; Ilya Sutskever; Oriol Vinyals; Lukasz Kaiser (ICLR (Poster), 2016)

Connecting Generative Adversarial Networks and Actor-Critic Methods. - David Pfau; Oriol Vinyals (CoRR, 2016)

Order Matters: Sequence to sequence for sets. - Oriol Vinyals; Samy Bengio; Manjunath Kudlur (ICLR (Poster), 2016)

Google's Neural Machine Translation System: Bridging the Gap between Human and Machine Translation. - Yonghui Wu; Mike Schuster; Zhifeng Chen; Quoc V. Le; Mohammad Norouzi 002; Wolfgang Macherey; Maxim Krikun; Yuan Cao 007; Qin Gao; Klaus Macherey; Jeff Klingner; Apurva Shah; et al. (CoRR, 2016)

Lip Reading Sentences in the Wild. - Joon Son Chung; Andrew W. Senior; Oriol Vinyals; Andrew Zisserman (CVPR, 2017)

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

Understanding deep learning requires rethinking generalization. - Chiyuan Zhang; Samy Bengio; Moritz Hardt; Benjamin Recht; Oriol Vinyals (ICLR, 2017)

Understanding Synthetic Gradients and Decoupled Neural Interfaces. - Wojciech Marian Czarnecki; Grzegorz Swirszcz; Max Jaderberg; Simon Osindero; Oriol Vinyals; Koray Kavukcuoglu (ICML, 2017)

Neural Message Passing for Quantum Chemistry. - Justin Gilmer; Samuel S. Schoenholz; Patrick F. Riley; Oriol Vinyals; George E. Dahl (ICML, 2017)

Decoupled Neural Interfaces using Synthetic Gradients. - Max Jaderberg; Wojciech Marian Czarnecki; Simon Osindero; Oriol Vinyals; Alex Graves; David Silver 001; Koray Kavukcuoglu (ICML, 2017)

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

Neural Episodic Control. - Alexander Pritzel; Benigno Uria; Sriram Srinivasan 005; Adrià Puigdomènech Badia; Oriol Vinyals; Demis Hassabis; Daan Wierstra; Charles Blundell (ICML, 2017)

Neural Discrete Representation Learning. - Aäron van den Oord; Oriol Vinyals; Koray Kavukcuoglu (NIPS, 2017)

Imagination-Augmented Agents for Deep Reinforcement Learning. - Sébastien Racanière; Theophane Weber; David P. Reichert; Lars Buesing; Arthur Guez; Danilo Jimenez Rezende; Adrià Puigdomènech Badia; Oriol Vinyals; Nicolas Heess; Yujia Li 001; Razvan Pascanu; Peter W. Battaglia; et al. (NIPS, 2017)

Bayesian Recurrent Neural Networks. - Meire Fortunato; Charles Blundell; Oriol Vinyals (CoRR, 2017)

Adversarial Evaluation of Dialogue Models. - Anjuli Kannan; Oriol Vinyals (CoRR, 2017)

Learning model-based planning from scratch. - Razvan Pascanu; Yujia Li 001; Oriol Vinyals; Nicolas Heess; Lars Buesing; Sébastien Racanière; David P. Reichert; Theophane Weber; Daan Wierstra; Peter W. Battaglia (CoRR, 2017)

Imagination-Augmented Agents for Deep Reinforcement Learning. - Theophane Weber; Sébastien Racanière; David P. Reichert; Lars Buesing; Arthur Guez; Danilo Jimenez Rezende; Adrià Puigdomènech Badia; Oriol Vinyals; Nicolas Heess; Yujia Li 001; Razvan Pascanu; Peter W. Battaglia; et al. (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)

Show and Tell: Lessons Learned from the 2015 MSCOCO Image Captioning Challenge. - Oriol Vinyals; Alexander Toshev; Samy Bengio; Dumitru Erhan (IEEE Trans. Pattern Anal. Mach. Intell., 2017)

Temporal Modeling Using Dilated Convolution and Gating for Voice-Activity-Detection. - Shuo-Yiin Chang; Bo Li 028; Gabor Simko; Tara N. Sainath; Anshuman Tripathi; Aäron van den Oord; Oriol Vinyals (ICASSP, 2018)

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

Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions. - Scott E. Reed; Yutian Chen 001; Thomas Paine; Aäron van den Oord; S. M. Ali Eslami; Danilo J. Rezende; Oriol Vinyals; Nando de Freitas (ICLR (Poster), 2018)

Memory-based Parameter Adaptation. - Pablo Sprechmann; Siddhant M. Jayakumar; Jack W. Rae; Alexander Pritzel; Adrià Puigdomènech Badia; Benigno Uria; Oriol Vinyals; Demis Hassabis; Razvan Pascanu; Charles Blundell (ICLR (Poster), 2018)

Synthesizing Programs for Images using Reinforced Adversarial Learning. - Yaroslav Ganin; Tejas Kulkarni; Igor Babuschkin; S. M. Ali Eslami; Oriol Vinyals (ICML, 2018)

Learning to Search with MCTSnets. - Arthur Guez; Theophane Weber; Ioannis Antonoglou; Karen Simonyan; Oriol Vinyals; Daan Wierstra; Rémi Munos; David Silver 001 (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)

Learning Implicit Generative Models with the Method of Learned Moments. - Suman V. Ravuri; Shakir Mohamed; Mihaela Rosca; Oriol Vinyals (ICML, 2018)

Relational recurrent neural networks. - Adam Santoro; Ryan Faulkner 001; David Raposo; Jack W. Rae; Mike Chrzanowski; Theophane Weber; Daan Wierstra; Oriol Vinyals; Razvan Pascanu; Timothy P. Lillicrap (NeurIPS, 2018)

Learning Fast Optimizers for Contextual Stochastic Integer Programs. - Vinod Nair; Dj Dvijotham; Iain Dunning; Oriol Vinyals (UAI, 2018)

Learning Deep Generative Models of Graphs. - Yujia Li 001; Oriol Vinyals; Chris Dyer; Razvan Pascanu; Peter W. Battaglia (CoRR, 2018)

A Study on Overfitting in Deep Reinforcement Learning. - Chiyuan Zhang; Oriol Vinyals; Rémi Munos; Samy Bengio (CoRR, 2018)

Relational inductive biases, deep learning, and graph networks. - Peter W. Battaglia; Jessica B. Hamrick; Victor Bapst; Alvaro Sanchez-Gonzalez; Vinícius Flores Zambaldi; Mateusz Malinowski; Andrea Tacchetti; David Raposo; Adam Santoro; Ryan Faulkner 001; Çaglar Gülçehre; H. Francis Song; et al. (CoRR, 2018)

Relational Deep Reinforcement Learning. - Vinícius Flores Zambaldi; David Raposo; Adam Santoro; Victor Bapst; Yujia Li 001; Igor Babuschkin; Karl Tuyls; David P. Reichert; Timothy P. Lillicrap; Edward Lockhart; Murray Shanahan; Victoria Langston; et al. (CoRR, 2018)

Representation Learning with Contrastive Predictive Coding. - Aäron van den Oord; Yazhe Li; Oriol Vinyals (CoRR, 2018)

Generating Diverse Programs with Instruction Conditioned Reinforced Adversarial Learning. - Aishwarya Agrawal; Mateusz Malinowski; Felix Hill; S. M. Ali Eslami; Oriol Vinyals; Tejas Kulkarni (CoRR, 2018)

Low Bit-rate Speech Coding with VQ-VAE and a WaveNet Decoder. - Cristina Gârbacea; Aäron van den Oord; Yazhe Li; Felicia S. C. Lim; Alejandro Luebs; Oriol Vinyals; Thomas C. Walters (ICASSP, 2019)

Sample Efficient Adaptive Text-to-Speech. - Yutian Chen 001; Yannis M. Assael; Brendan Shillingford; David Budden; Scott E. Reed; Heiga Zen; Quan Wang; Luis C. Cobo; Andrew Trask; Ben Laurie; Çaglar Gülçehre; Aäron van den Oord; et al. (ICLR (Poster), 2019)

Universal Transformers. - Mostafa Dehghani 001; Stephan Gouws; Oriol Vinyals; Jakob Uszkoreit; Lukasz Kaiser (ICLR (Poster), 2019)

Attentive Neural Processes. - Hyunjik Kim; Andriy Mnih; Jonathan Schwarz; Marta Garnelo; S. M. Ali Eslami; Dan Rosenbaum; Oriol Vinyals; Yee Whye Teh (ICLR (Poster), 2019)

Preventing Posterior Collapse with delta-VAEs. - Ali Razavi; Aäron van den Oord; Ben Poole; Oriol Vinyals (ICLR (Poster), 2019)

Generating Diverse High-Resolution Images with VQ-VAE. - Ali Razavi; Aäron van den Oord; Oriol Vinyals (DGS@ICLR, 2019)

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

Deep reinforcement learning with relational inductive biases. - Vinícius Flores Zambaldi; David Raposo; Adam Santoro; Victor Bapst; Yujia Li 001; Igor Babuschkin; Karl Tuyls; David P. Reichert; Timothy P. Lillicrap; Edward Lockhart; Murray Shanahan; Victoria Langston; et al. (ICLR (Poster), 2019)

Graph Matching Networks for Learning the Similarity of Graph Structured Objects. - Yujia Li 001; Chenjie Gu; Thomas Dullien; Oriol Vinyals; Pushmeet Kohli (ICML, 2019)

Retrospective Analysis of the 2019 MineRL Competition on Sample Efficient Reinforcement Learning. - Stephanie Milani; Nicholay Topin; Brandon Houghton; William H. Guss; Sharada P. Mohanty; Keisuke Nakata; Oriol Vinyals; Noboru Sean Kuno (NeurIPS (Competition and Demos), 2019)

Classification Accuracy Score for Conditional Generative Models. - Suman V. Ravuri; Oriol Vinyals (NeurIPS, 2019)

Generating Diverse High-Fidelity Images with VQ-VAE-2. - Ali Razavi; Aäron van den Oord; Oriol Vinyals (NeurIPS, 2019)

REGAL: Transfer Learning For Fast Optimization of Computation Graphs. - Aditya Paliwal; Felix Gimeno; Vinod Nair; Yujia Li 001; Miles Lubin; Pushmeet Kohli; Oriol Vinyals (CoRR, 2019)

Unsupervised Doodling and Painting with Improved SPIRAL. - John F. J. Mellor; Eunbyung Park; Yaroslav Ganin; Igor Babuschkin; Tejas Kulkarni; Dan Rosenbaum; Andy Ballard; Theophane Weber; Oriol Vinyals; S. M. Ali Eslami (CoRR, 2019)

Grandmaster level in StarCraft II using multi-agent reinforcement learning. - Oriol Vinyals; Igor Babuschkin; Wojciech M. Czarnecki; Michaël Mathieu; Andrew Dudzik; Junyoung Chung; David H. Choi; Richard Powell; Timo Ewalds; Petko Georgiev; Junhyuk Oh; Dan Horgan; et al. (Nat., 2019)

Reinforced Genetic Algorithm Learning for Optimizing Computation Graphs. - Aditya Paliwal; Felix Gimeno; Vinod Nair; Yujia Li 001; Miles Lubin; Pushmeet Kohli; Oriol Vinyals (ICLR, 2020)

Rapid Learning or Feature Reuse? Towards Understanding the Effectiveness of MAML. - Aniruddh Raghu; Maithra Raghu; Samy Bengio; Oriol Vinyals (ICLR, 2020)

Pointer Graph Networks. - Petar Velickovic; Lars Buesing; Matthew C. Overlan; Razvan Pascanu; Oriol Vinyals; Charles Blundell (NeurIPS, 2020)

Strong Generalization and Efficiency in Neural Programs. - Yujia Li 001; Felix Gimeno; Pushmeet Kohli; Oriol Vinyals (CoRR, 2020)

AlignNet: Unsupervised Entity Alignment. - Antonia Creswell; Kyriacos Nikiforou; Oriol Vinyals; Andre Saraiva 001; Rishabh Kabra; Loic Matthey; Chris Burgess 001; Malcolm Reynolds; Richard Tanburn; Marta Garnelo; Murray Shanahan (CoRR, 2020)

Solving Mixed Integer Programs Using Neural Networks. - Vinod Nair; Sergey Bartunov; Felix Gimeno; Ingrid von Glehn; Pawel Lichocki; Ivan Lobov; Brendan O'Donoghue; Nicolas Sonnerat; Christian Tjandraatmadja; Pengming Wang 001; Ravichandra Addanki; Tharindi Hapuarachchi; et al. (CoRR, 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)

Efficient Visual Pretraining with Contrastive Detection. - Olivier J. Hénaff; Skanda Koppula; Jean-Baptiste Alayrac; Aäron van den Oord; Oriol Vinyals; João Carreira 001 (ICCV, 2021)

Perceiver: General Perception with Iterative Attention. - Andrew Jaegle; Felix Gimeno; Andy Brock; Oriol Vinyals; Andrew Zisserman; João Carreira 001 (ICML, 2021)

Vector Quantized Models for Planning. - Sherjil Ozair; Yazhe Li; Ali Razavi; Ioannis Antonoglou; Aäron van den Oord; Oriol Vinyals (ICML, 2021)

Multimodal Few-Shot Learning with Frozen Language Models. - Maria Tsimpoukelli; Jacob Menick; Serkan Cabi; S. M. Ali Eslami; Oriol Vinyals; Felix Hill (NeurIPS, 2021)

Understanding deep learning (still) requires rethinking generalization. - Chiyuan Zhang; Samy Bengio; Moritz Hardt; Benjamin Recht; Oriol Vinyals (Commun. ACM, 2021)

The MineRL 2020 Competition on Sample Efficient Reinforcement Learning using Human Priors. - William H. Guss; Mario Ynocente Castro; Sam Devlin; Brandon Houghton; Noboru Sean Kuno; Crissman Loomis; Stephanie Milani; Sharada P. Mohanty; Keisuke Nakata; Ruslan Salakhutdinov; John Schulman; Shinya Shiroshita; et al. (CoRR, 2021)

The Benchmark Lottery. - Mostafa Dehghani 001; Yi Tay; Alexey A. Gritsenko; Zhe Zhao 001; Neil Houlsby; Fernando Diaz 001; Donald Metzler; Oriol Vinyals (CoRR, 2021)

WikiGraphs: A Wikipedia Text - Knowledge Graph Paired Dataset. - Luyu Wang; Yujia Li 001; Özlem Aslan; Oriol Vinyals (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)

Non-isotropy Regularization for Proxy-based Deep Metric Learning. - Karsten Roth; Oriol Vinyals; Zeynep Akata (CVPR, 2022)

Integrating Language Guidance into Vision-based Deep Metric Learning. - Karsten Roth; Oriol Vinyals; Zeynep Akata (CVPR, 2022)

Perceiver IO: A General Architecture for Structured Inputs & Outputs. - Andrew Jaegle; Sebastian Borgeaud; Jean-Baptiste Alayrac; Carl Doersch; Catalin Ionescu; David Ding; Skanda Koppula; Daniel Zoran; Andrew Brock; Evan Shelhamer; Olivier J. Hénaff; Matthew M. Botvinick; et al. (ICLR, 2022)

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)

General-purpose, long-context autoregressive modeling with Perceiver AR. - Curtis Hawthorne; Andrew Jaegle; Catalina Cangea; Sebastian Borgeaud; Charlie Nash; Mateusz Malinowski; Sander Dieleman; Oriol Vinyals; Matthew M. Botvinick; Ian Simon; Hannah Sheahan; Neil Zeghidour; 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)

MuZero with Self-competition for Rate Control in VP9 Video Compression. - Amol Mandhane; Anton Zhernov; Maribeth Rauh; Chenjie Gu; Miaosen Wang; Flora Xue; Wendy Shang; Derek Pang; Rene Claus; Ching-Han Chiang; Cheng Chen; Jingning Han; 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)

Competition-Level Code Generation with AlphaCode. - Yujia Li 001; David H. Choi; Junyoung Chung; Nate Kushman; Julian Schrittwieser; Rémi Leblond; Tom Eccles; James Keeling; Felix Gimeno; Agustin Dal Lago; Thomas Hubert; Peter Choy; 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)

GraphCast: Learning skillful medium-range global weather forecasting. - Rémi Lam; Alvaro Sanchez-Gonzalez; Matthew Willson; Peter Wirnsberger; Meire Fortunato; Alexander Pritzel; Suman V. Ravuri; Timo Ewalds; Ferran Alet; Zach Eaton-Rosen; Weihua Hu; Alexander Merose; et al. (CoRR, 2022)

Deep Audio-Visual Speech Recognition. - Triantafyllos Afouras; Joon Son Chung; Andrew W. Senior; Oriol Vinyals; Andrew Zisserman (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

Guest Editorial: Non-Euclidean Machine Learning. - Stefanos Zafeiriou; Michael M. Bronstein; Taco Cohen; Oriol Vinyals; Le Song; Jure Leskovec; Pietro Liò; Joan Bruna; Marco Gori (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

A Generalist Agent. - Scott E. Reed; Konrad Zolna; Emilio Parisotto; Sergio Gómez Colmenarejo; Alexander Novikov 001; Gabriel Barth-Maron; Mai Gimenez; Yury Sulsky; Jackie Kay; Jost Tobias Springenberg; Tom Eccles; Jake Bruce; et al. (Trans. Mach. Learn. Res., 2022)

Emergent Abilities of Large Language Models. - Jason Wei; Yi Tay; Rishi Bommasani; Colin Raffel; Barret Zoph; Sebastian Borgeaud; Dani Yogatama; Maarten Bosma; Denny Zhou; Donald Metzler; Ed H. Chi; Tatsunori Hashimoto; et al. (Trans. Mach. Learn. Res., 2022)

Waffling around for Performance: Visual Classification with Random Words and Broad Concepts. - Karsten Roth; Jae-Myung Kim; A. Sophia Koepke; Oriol Vinyals; Cordelia Schmid; Zeynep Akata (ICCV, 2023)

Optimizing Memory Mapping Using Deep Reinforcement Learning. - Pengming Wang 001; Mikita Sazanovich; Berkin Ilbeyi; Phitchaya Mangpo Phothilimthana; Manish Purohit; Han Yang Tay; Ngân Vu; Miaosen Wang; Cosmin Paduraru; Edouard Leurent; Anton Zhernov; Julian Schrittwieser; et al. (CoRR, 2023)

AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning. - Michaël Mathieu; Sherjil Ozair; Srivatsan Srinivasan; Çaglar Gülçehre; Shangtong Zhang; Ray Jiang; Tom Le Paine; Richard Powell; Konrad Zolna; Julian Schrittwieser; David H. Choi; Petko Georgiev; et al. (CoRR, 2023)

Faster sorting algorithms discovered using deep reinforcement learning. - Daniel J. Mankowitz; Andrea Michi; Anton Zhernov; Marco Gelmi; Marco Selvi; Cosmin Paduraru; Edouard Leurent; Shariq Iqbal; Jean-Baptiste Lespiau; Alex Ahern; Thomas Köppe; Kevin Millikin; et al. (Nat., 2023)

Fantastic Gains and Where to Find Them: On the Existence and Prospect of General Knowledge Transfer between Any Pretrained Model. - Karsten Roth; Lukas Thede; A. Sophia Koepke; Oriol Vinyals; Olivier J. Hénaff; Zeynep Akata (ICLR, 2024)

A Practitioner's Guide to Real-World Continual Multimodal Pretraining. - Vishaal Udandarao; Karsten Roth; Sebastian Dziadzio; Ameya Prabhu; Mehdi Cherti; Oriol Vinyals; Olivier J. Hénaff; Samuel Albanie; Zeynep Akata; Matthias Bethge (NeurIPS, 2024)

Capabilities of Gemini Models in Medicine. - Khaled Saab 003; Tao Tu 001; Wei-Hung Weng; Ryutaro Tanno; David Stutz; Ellery Wulczyn; Fan Zhang; Tim Strother; Chunjong Park; Elahe Vedadi; Juanma Zambrano Chaves; Szu-Yeu Hu; et al. (CoRR, 2024)

A Practitioner's Guide to Continual Multimodal Pretraining. - Karsten Roth; Vishaal Udandarao; Sebastian Dziadzio; Ameya Prabhu; Mehdi Cherti; Oriol Vinyals; Olivier J. Hénaff; Samuel Albanie; Matthias Bethge; Zeynep Akata (CoRR, 2024)

Gemma 3 Technical Report. - Aishwarya Kamath; Johan Ferret; Shreya Pathak; Nino Vieillard; Ramona Merhej; Sarah Perrin; Tatiana Matejovicova; Alexandre Ramé; Morgane Rivière; Louis Rouillard; Thomas Mesnard; Geoffrey Cideron; et al. (CoRR, 2025)

Gemini Robotics: Bringing AI into the Physical World. - Gemini Robotics Team; Saminda Abeyruwan; Joshua Ainslie; Jean-Baptiste Alayrac; Montserrat Gonzalez Arenas; Travis Armstrong; Ashwin Balakrishna; Robert Baruch; Maria Bauzá 001; Michiel Blokzijl; Steven Bohez; Konstantinos Bousmalis; et al. (CoRR, 2025)