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High Accuracy Protein Structure Prediction Using Deep Learning
John Jumper*, Richard Evans*, Alexander Pritzel*, Tim Green*, Michael Figurnov*, Kathryn Tunyasuvunakool*, Olaf Ronneberger*, Russ Bates*, Augustin Žídek*, Alex Bridgland*, Clemens Meyer*, Simon A A Kohl*, Anna Potapenko*, Andrew J Ballard*, Andrew Cowie*, Bernardino Romera-Paredes*, Stanislav Nikolov*, Rishub Jain*, Jonas Adler, Trevor Back, Stig Petersen, David Reiman, Martin Steinegger, Michalina Pacholska, David Silver, Oriol Vinyals, Andrew W Senior, Koray Kavukcuoglu, Pushmeet Kohli, Demis Hassabis
Fourteenth Critical Assessment of Techniques for Protein Structure Prediction (Abstract Book), 30 November - 4 December 2020
blog post /
abstract
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Monte Carlo Gradient Estimation in Machine Learning
Shakir Mohamed*, Mihaela Rosca*, Michael Figurnov*, Andriy Mnih*
JMLR, 2020
arxiv /
code (TensorFlow) /
code (JAX)
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Tensor Train Decomposition on TensorFlow (T3F)
Alexander Novikov, Pavel Izmailov, Valentin Khrulkov, Michael Figurnov, Ivan V Oseledets
JMLR Open Source Software, 2020
arxiv /
code (TensorFlow) /
Python package
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Measure-Valued Derivatives for Approximate Bayesian Inference
Mihaela Rosca*, Michael Figurnov*, Shakir Mohamed, Andriy Mnih
Bayesian Deep Learning (NeurIPS Workshop) oral, 2019
paper /
talk (11 minutes) /
code (TensorFlow) /
code (JAX)
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Variational Autoencoder with Arbitrary Conditioning
Oleg Ivanov, Michael Figurnov, Dmitry Vetrov
ICLR, 2019
arxiv /
poster /
code
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Implicit reparameterization gradients
Michael Figurnov, Shakir Mohamed, Andriy Mnih
NeurIPS spotlight, 2018
arxiv /
poster /
spotlight video (3 minutes) /
spotlight slides /
code is integrated into TensorFlow and TensorFlow Probability, eg:
Gamma distribution,
Beta distribution,
Dirichlet distribution,
Von Mises distribution,
mixture of distributions (set reparameterize=True)
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Probabilistic Adaptive Computation Time
Michael Figurnov, Artem Sobolev, Dmitry Vetrov
Bulletin of the Polish Academy of Sciences; Deep Learning: Theory and Practice, 2018
paper /
arxiv (slightly older version)
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Spatially Adaptive Computation Time for Residual Networks
Michael Figurnov, Maxwell D. Collins, Yukun Zhu, Li Zhang, Jonathan Huang, Dmitry Vetrov, Ruslan Salakhutdinov
CVPR, 2017
arxiv /
poster /
code (TensorFlow)
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PerforatedCNNs: Acceleration through Elimination of Redundant Convolutions
Michael Figurnov, Aijan Ibraimova, Dmitry Vetrov, Pushmeet Kohli
NeurIPS, 2016
arxiv /
poster /
code (Caffe) /
code (MatConvNet)
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Robust Variational Inference
Michael Figurnov, Kirill Struminsky, Dmitry Vetrov
Advances in Approximate Bayesian Inference, NeurIPS, 2016
arxiv
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