Overlap versus Imbalance. - Misha Denil; Thomas Trappenberg (Canadian AI, 2010)

A Characterization of the Combined Effects of Overlap and Imbalance on the SVM Classifier - Misha Denil; Thomas Trappenberg (CoRR, 2011)

Recklessly Approximate Sparse Coding - Misha Denil; Nando de Freitas (CoRR, 2012)

Learning Where to Attend with Deep Architectures for Image Tracking. - Misha Denil; Loris Bazzani; Hugo Larochelle; Nando de Freitas (Neural Comput., 2012)

Consistency of Online Random Forests. - Misha Denil; David Matheson; Nando de Freitas (ICML (3), 2013)

Predicting Parameters in Deep Learning. - Misha Denil; Babak Shakibi; Laurent Dinh; Marc'Aurelio Ranzato; Nando de Freitas (NIPS, 2013)

Narrowing the Gap: Random Forests In Theory and In Practice. - Misha Denil; David Matheson; Nando de Freitas (ICML, 2014)

Linear and Parallel Learning of Markov Random Fields. - Yariv Dror Mizrahi; Misha Denil; Nando de Freitas (ICML, 2014)

Distributed Parameter Estimation in Probabilistic Graphical Models. - Yariv Dror Mizrahi; Misha Denil; Nando de Freitas (NIPS, 2014)

Extraction of Salient Sentences from Labelled Documents. - Misha Denil; Alban Demiraj; Nando de Freitas (CoRR, 2014)

Modelling, Visualising and Summarising Documents with a Single Convolutional Neural Network. - Misha Denil; Alban Demiraj; Nal Kalchbrenner; Phil Blunsom; Nando de Freitas (CoRR, 2014)

Deep Multi-Instance Transfer Learning. - Dimitrios Kotzias; Misha Denil; Phil Blunsom; Nando de Freitas (CoRR, 2014)

Deep Apprenticeship Learning for Playing Video Games. - Miroslav Bogdanovic; Dejan Markovikj; Misha Denil; Nando de Freitas (AAAI Workshop: Learning for General Competency in Video Games, 2015)

Deep Fried Convnets. - Zichao Yang; Marcin Moczulski; Misha Denil; Nando de Freitas; Alexander J. Smola; Le Song; Ziyu Wang 001 (ICCV, 2015)

From Group to Individual Labels Using Deep Features. - Dimitrios Kotzias; Misha Denil; Nando de Freitas; Padhraic Smyth (KDD, 2015)

Noisy Activation Functions. - Çaglar Gülçehre; Marcin Moczulski; Misha Denil; Yoshua Bengio (ICML, 2016)

Learning to learn by gradient descent by gradient descent. - Marcin Andrychowicz; Misha Denil; Sergio Gomez Colmenarejo; Matthew W. Hoffman; David Pfau; Tom Schaul; Nando de Freitas (NIPS, 2016)

Learning to Learn for Global Optimization of Black Box Functions. - Yutian Chen 001; Matthew W. Hoffman; Sergio Gomez Colmenarejo; Misha Denil; Timothy P. Lillicrap; Nando de Freitas (CoRR, 2016)

ACDC: A Structured Efficient Linear Layer. - Marcin Moczulski; Misha Denil; Jeremy Appleyard; Nando de Freitas (ICLR (Poster), 2016)

The Intentional Unintentional Agent: Learning to Solve Many Continuous Control Tasks Simultaneously. - Serkan Cabi; Sergio Gomez Colmenarejo; Matthew W. Hoffman; Misha Denil; Ziyu Wang 001; Nando de Freitas (CoRL, 2017)

Learning to Perform Physics Experiments via Deep Reinforcement Learning. - Misha Denil; Pulkit Agrawal 001; Tejas D. Kulkarni; Tom Erez; Peter W. Battaglia; Nando de Freitas (ICLR (Poster), 2017)

Learning to Navigate in Complex Environments. - Piotr Mirowski; Razvan Pascanu; Fabio Viola; Hubert Soyer; Andy Ballard; Andrea Banino; Misha Denil; Ross Goroshin; Laurent Sifre; Koray Kavukcuoglu; Dharshan Kumaran; Raia Hadsell (ICLR (Poster), 2017)

Learning to Learn without Gradient Descent by Gradient Descent. - Yutian Chen 001; Matthew W. Hoffman; Sergio Gomez Colmenarejo; Misha Denil; Timothy P. Lillicrap; Matthew M. Botvinick; Nando de Freitas (ICML, 2017)

Learned Optimizers that Scale and Generalize. - Olga Wichrowska; Niru Maheswaranathan; Matthew W. Hoffman; Sergio Gomez Colmenarejo; Misha Denil; Nando de Freitas; Jascha Sohl-Dickstein (ICML, 2017)

Programmable Agents. - Misha Denil; Sergio Gomez Colmenarejo; Serkan Cabi; David Saxton; Nando de Freitas (CoRR, 2017)

Learning Awareness Models. - Brandon Amos; Laurent Dinh; Serkan Cabi; Thomas Rothörl; Sergio Gomez Colmenarejo; Alistair Muldal; Tom Erez; Yuval Tassa; Nando de Freitas; Misha Denil (ICLR (Poster), 2018)

Hyperbolic Attention Networks. - Çaglar Gülçehre; Misha Denil; Mateusz Malinowski; Ali Razavi; Razvan Pascanu; Karl Moritz Hermann; Peter W. Battaglia; Victor Bapst; David Raposo; Adam Santoro; Nando de Freitas (ICLR (Poster), 2019)

Large-Scale Visual Speech Recognition. - Brendan Shillingford; Yannis M. Assael; Matthew W. Hoffman; Thomas Paine; Cían Hughes; Utsav Prabhu; Hank Liao; Hasim Sak; Kanishka Rao; Lorrayne Bennett; Marie Mulville; Misha Denil; et al. (INTERSPEECH, 2019)

A Framework for Data-Driven Robotics. - Serkan Cabi; Sergio Gómez Colmenarejo; Alexander Novikov 001; Ksenia Konyushkova; Scott E. Reed; Rae Jeong; Konrad Zolna; Yusuf Aytar; David Budden; Mel Vecerík; Oleg Sushkov; David Barker; et al. (CoRR, 2019)

Positive-Unlabeled Reward Learning. - Danfei Xu; Misha Denil (CoRL, 2020)

Task-Relevant Adversarial Imitation Learning. - Konrad Zolna; Scott E. Reed; Alexander Novikov 001; Sergio Gómez Colmenarejo; David Budden; Serkan Cabi; Misha Denil; Nando de Freitas; Ziyu Wang 001 (CoRL, 2020)

Making Efficient Use of Demonstrations to Solve Hard Exploration Problems. - Çaglar Gülçehre; Tom Le Paine; Bobak Shahriari; Misha Denil; Matt Hoffman 001; Hubert Soyer; Richard Tanburn; Steven Kapturowski; Neil C. Rabinowitz; Duncan Williams; Gabriel Barth-Maron; Ziyu Wang 001; et al. (ICLR, 2020)

Scaling data-driven robotics with reward sketching and batch reinforcement learning. - Serkan Cabi; Sergio Gómez Colmenarejo; Alexander Novikov 001; Ksenia Konyushkova; Scott E. Reed; Rae Jeong; Konrad Zolna; Yusuf Aytar; David Budden; Mel Vecerík; Oleg Sushkov; David Barker; et al. (Robotics: Science and Systems, 2020)

Large-scale multilingual audio visual dubbing. - Yi Yang 007; Brendan Shillingford; Yannis M. Assael; Miaosen Wang; Wendi Liu; Yutian Chen 001; Yu Zhang; Eren Sezener; Luis C. Cobo; Misha Denil; Yusuf Aytar; Nando de Freitas (CoRR, 2020)

Offline Learning from Demonstrations and Unlabeled Experience. - Konrad Zolna; Alexander Novikov 001; Ksenia Konyushkova; Çaglar Gülçehre; Ziyu Wang 001; Yusuf Aytar; Misha Denil; Nando de Freitas; Scott E. Reed (CoRR, 2020)

Active Offline Policy Selection. - Ksenia Konyushkova; Yutian Chen 001; Thomas Paine; Çaglar Gülçehre; Cosmin Paduraru; Daniel J. Mankowitz; Misha Denil; Nando de Freitas (NeurIPS, 2021)

Interactive decoding of words from visual speech recognition models. - Brendan Shillingford; Yannis M. Assael; Misha Denil (CoRR, 2021)

Vision-Language Models as Success Detectors. - Yuqing Du; Ksenia Konyushkova; Misha Denil; Akhil Raju; Jessica Landon; Felix Hill; Nando de Freitas; Serkan Cabi (CoLLAs, 2023)

π2vec: Policy Representations with Successor Features. - Gianluca Scarpellini; Ksenia Konyushkova; Claudio Fantacci; Tom Le Paine; Yutian Chen 001; Misha Denil (CoRR, 2023)

RoboCat: A Self-Improving Foundation Agent for Robotic Manipulation. - Konstantinos Bousmalis; Giulia Vezzani; Dushyant Rao; Coline Devin; Alex X. Lee; Maria Bauzá 001; Todor Davchev; Yuxiang Zhou; Agrim Gupta; Akhil Raju; Antoine Laurens; Claudio Fantacci; et al. (CoRR, 2023)

π2vec: Policy Representation with Successor Features. - Gianluca Scarpellini; Ksenia Konyushkova; Claudio Fantacci; Thomas Paine; Yutian Chen 001; Misha Denil (ICLR, 2024)

Rapid Object Annotation. - Misha Denil (CoRR, 2024)

RoboCat: A Self-Improving Generalist Agent for Robotic Manipulation. - Konstantinos Bousmalis; Giulia Vezzani; Dushyant Rao; Coline Manon Devin; Alex X. Lee; Maria Bauzá Villalonga; Todor Davchev; Yuxiang Zhou; Agrim Gupta; Akhil Raju; Antoine Laurens; Claudio Fantacci; et al. (Trans. Mach. Learn. Res., 2024)

Vision-Language Model Dialog Games for Self-Improvement. - Ksenia Konyushkova; Christos Kaplanis; Serkan Cabi; Misha Denil (CoRR, 2025)