Ryota Tomioka

A generative model for inorganic materials design

Claudio Zeni, Robert Pinsler, Daniel Zügner, Andrew Fowler, Matthew Horton, Xiang Fu, Zilong Wang, Aliaksandra Shysheya, Jonathan Crabbé, Shoko Ueda, Roberto Sordillo, Lixin Sun, Jake Smith, Bichlien Nguyen, Hannes Schulz, Sarah Lewis, Chin-Wei Huang, Ziheng Lu, Yichi Zhou, Han Yang, Hongxia Hao, Jielan Li, Chunlei Yang, Wenjie Li, Ryota Tomioka, Tian Xie

Nature | January 2025

Publication

MatterGen: a generative model for inorganic materials design

Claudio Zeni, Robert Pinsler, Daniel Zügner, Andrew Fowler, Matthew Horton, Xiang Fu, Sasha Shysheya, Jonathan Crabbé, Lixin Sun, Jake Smith, Ryota Tomioka, Tian Xie

December 2023

PDF Publication Video Video Video Github

Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck

Marco Federici, Patrick Forr'e, Ryota Tomioka, Bastiaan S. Veeling

ICLR 2024 | September 2023

DOI Publication

Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics

Leon Klein, Andrew Y. K. Foong, Tor Erlend Fjelde, Bruno Mlodozeniec, Marc Brockschmidt, Sebastian Nowozin, Frank Noé, Ryota Tomioka

NeurIPS 2023 | February 2023

Publication

An Information-theoretic Approach to Distribution Shifts

Marco Federici, Ryota Tomioka, Patrick Forré

2021 Neural Information Processing Systems | November 2021

Publication

DistIR: An Intermediate Representation for Optimizing Distributed Neural Networks

Keshav Santhanam, Siddharth Krishna, Ryota Tomioka, Andrew Fitzgibbon, Tim Harris

EuroMLSys '21: Proceedings of the 1st Workshop on Machine Learning and Systems | April 2021

Publication Github

Regularized Policies are Reward Robust

Hisham Husain, Kamil Ciosek, Ryota Tomioka

Proceedings of The 24th International Conference on Artificial Intelligence and Statistics | April 2021

Publication

On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them

Chen Liu, Mathieu Salzmann, Tao Lin, Ryota Tomioka, Sabine Süsstrunk

NeurIPS 2020 | December 2020

Publication

Conservative Uncertainty Estimation By Fitting Prior Networks

Kamil Ciosek, Vincent Fortuin, Ryota Tomioka, Katja Hofmann, Richard Turner

Eighth International Conference on Learning Representations (ICLR) | April 2020

Publication PDF Github Project Project

On Certifying Non-Uniform Bounds against Adversarial Attacks

Chen Liu, Ryota Tomioka, Volkan Cevher

International Conference on Machine Learning (ICML) | June 2019

Publication

Depth and nonlinearity induce implicit exploration for RL

Justas Dauparas, Ryota Tomioka, Katja Hofmann

ICML workshop on Exploration in RL | July 2018

Publication

Multi-Level Variational Autoencoder: Learning Disentangled Representations from Grouped Observations

Diane Bouchacourt, Ryota Tomioka, Sebastian Nowozin

AAAI 2018 | February 2018

Publication Project

QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding

Dan Alistarh, Demjan Grubic, Jerry Li, Ryota Tomioka, Milan Vojnovic

Advances in Neural Information Processing Systems 30 (NIPS 2017) | December 2017

Publication

AMPNet: Asynchronous Model-Parallel Training for Dynamic Neural Networks

Alexander Gaunt, Matthew Johnson, Maik Riechert, Daniel Tarlow, Ryota Tomioka, Dimitrios Vytiniotis, Sam Webster

arXiv preprint arXiv:1705.09786 | May 2017

Publication Publication

Gaussian Attention Model and Its Application to Knowledge Base Embedding and Question Answering

Liwen Zhang, John Winn, Ryota Tomioka

MSR-TR-2016-1141 | November 2016

Published by Microsoft

Publication

f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization

Sebastian Nowozin, Botond Cseke, Ryota Tomioka

Advances in Neural Information Processing Systems 29 (NIPS 2016) | October 2016

Publication Publication Publication Project

Data-Dependent Path Normalization in Neural Networks

Behnam Neyshabur, Ryota Tomioka, Ruslan Salakhutdinov, Nathan Srebro

ICLR 2016 | November 2015

Publication

A generative model for inorganic materials design

Claudio Zeni, Robert Pinsler, Daniel Zügner, Andrew Fowler, Matthew Horton, Xiang Fu, Zilong Wang, Aliaksandra Shysheya, Jonathan Crabbé, Shoko Ueda, Roberto Sordillo, Lixin Sun, Jake Smith, Bichlien Nguyen, Hannes Schulz, Sarah Lewis, Chin-Wei Huang, Ziheng Lu, Yichi Zhou, Han Yang, Hongxia Hao, Jielan Li, Chunlei Yang, Wenjie Li, Ryota Tomioka, Tian Xie

Nature | January 2025

Publication

MatterGen: a generative model for inorganic materials design

Claudio Zeni, Robert Pinsler, Daniel Zügner, Andrew Fowler, Matthew Horton, Xiang Fu, Sasha Shysheya, Jonathan Crabbé, Lixin Sun, Jake Smith, Ryota Tomioka, Tian Xie

December 2023

PDF Publication Video Video Video Github

Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck

Marco Federici, Patrick Forr'e, Ryota Tomioka, Bastiaan S. Veeling

ICLR 2024 | September 2023

DOI Publication

Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics

Leon Klein, Andrew Y. K. Foong, Tor Erlend Fjelde, Bruno Mlodozeniec, Marc Brockschmidt, Sebastian Nowozin, Frank Noé, Ryota Tomioka

NeurIPS 2023 | February 2023

Publication

An Information-theoretic Approach to Distribution Shifts

Marco Federici, Ryota Tomioka, Patrick Forré

2021 Neural Information Processing Systems | November 2021

Publication

Regularized Policies are Reward Robust

Hisham Husain, Kamil Ciosek, Ryota Tomioka

Proceedings of The 24th International Conference on Artificial Intelligence and Statistics | April 2021

Publication

DistIR: An Intermediate Representation for Optimizing Distributed Neural Networks

Keshav Santhanam, Siddharth Krishna, Ryota Tomioka, Andrew Fitzgibbon, Tim Harris

EuroMLSys '21: Proceedings of the 1st Workshop on Machine Learning and Systems | April 2021

Publication Github

On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them

Chen Liu, Mathieu Salzmann, Tao Lin, Ryota Tomioka, Sabine Süsstrunk

NeurIPS 2020 | December 2020

Publication

Conservative Uncertainty Estimation By Fitting Prior Networks

Kamil Ciosek, Vincent Fortuin, Ryota Tomioka, Katja Hofmann, Richard Turner

Eighth International Conference on Learning Representations (ICLR) | April 2020

Publication PDF Github Project Project

On Certifying Non-Uniform Bounds against Adversarial Attacks

Chen Liu, Ryota Tomioka, Volkan Cevher

International Conference on Machine Learning (ICML) | June 2019

Publication

Depth and nonlinearity induce implicit exploration for RL

Justas Dauparas, Ryota Tomioka, Katja Hofmann

ICML workshop on Exploration in RL | July 2018

Publication

Multi-Level Variational Autoencoder: Learning Disentangled Representations from Grouped Observations

Diane Bouchacourt, Ryota Tomioka, Sebastian Nowozin

AAAI 2018 | February 2018

Publication Project

QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding

Dan Alistarh, Demjan Grubic, Jerry Li, Ryota Tomioka, Milan Vojnovic

Advances in Neural Information Processing Systems 30 (NIPS 2017) | December 2017

Publication

AMPNet: Asynchronous Model-Parallel Training for Dynamic Neural Networks

Alexander Gaunt, Matthew Johnson, Maik Riechert, Daniel Tarlow, Ryota Tomioka, Dimitrios Vytiniotis, Sam Webster

arXiv preprint arXiv:1705.09786 | May 2017

Publication Publication

Gaussian Attention Model and Its Application to Knowledge Base Embedding and Question Answering

Liwen Zhang, John Winn, Ryota Tomioka

MSR-TR-2016-1141 | November 2016

Published by Microsoft

Publication

f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization

Sebastian Nowozin, Botond Cseke, Ryota Tomioka

Advances in Neural Information Processing Systems 29 (NIPS 2016) | October 2016

Publication Publication Publication Project

Data-Dependent Path Normalization in Neural Networks

Behnam Neyshabur, Ryota Tomioka, Ruslan Salakhutdinov, Nathan Srebro

ICLR 2016 | November 2015

Publication

A generative model for inorganic materials design

Claudio Zeni, Robert Pinsler, Daniel Zügner, Andrew Fowler, Matthew Horton, Xiang Fu, Zilong Wang, Aliaksandra Shysheya, Jonathan Crabbé, Shoko Ueda, Roberto Sordillo, Lixin Sun, Jake Smith, Bichlien Nguyen, Hannes Schulz, Sarah Lewis, Chin-Wei Huang, Ziheng Lu, Yichi Zhou, Han Yang, Hongxia Hao, Jielan Li, Chunlei Yang, Wenjie Li, Ryota Tomioka, Tian Xie

Nature | January 2025

Publication

A generative model for inorganic materials design

Claudio Zeni, Robert Pinsler, Daniel Zügner, Andrew Fowler, Matthew Horton, Xiang Fu, Zilong Wang, Aliaksandra Shysheya, Jonathan Crabbé, Shoko Ueda, Roberto Sordillo, Lixin Sun, Jake Smith, Bichlien Nguyen, Hannes Schulz, Sarah Lewis, Chin-Wei Huang, Ziheng Lu, Yichi Zhou, Han Yang, Hongxia Hao, Jielan Li, Chunlei Yang, Wenjie Li, Ryota Tomioka, Tian Xie

Nature | January 2025

Publication

AMPNet: Asynchronous Model-Parallel Training for Dynamic Neural Networks

Alexander Gaunt, Matthew Johnson, Maik Riechert, Daniel Tarlow, Ryota Tomioka, Dimitrios Vytiniotis, Sam Webster

arXiv preprint arXiv:1705.09786 | May 2017

Publication Publication

Latent Representation and Simulation of Markov Processes via Time-Lagged Information Bottleneck

Marco Federici, Patrick Forr'e, Ryota Tomioka, Bastiaan S. Veeling

ICLR 2024 | September 2023

DOI Publication

Timewarp: Transferable Acceleration of Molecular Dynamics by Learning Time-Coarsened Dynamics

Leon Klein, Andrew Y. K. Foong, Tor Erlend Fjelde, Bruno Mlodozeniec, Marc Brockschmidt, Sebastian Nowozin, Frank Noé, Ryota Tomioka

NeurIPS 2023 | February 2023

Publication

An Information-theoretic Approach to Distribution Shifts

Marco Federici, Ryota Tomioka, Patrick Forré

2021 Neural Information Processing Systems | November 2021

Publication

Regularized Policies are Reward Robust

Hisham Husain, Kamil Ciosek, Ryota Tomioka

Proceedings of The 24th International Conference on Artificial Intelligence and Statistics | April 2021

Publication

DistIR: An Intermediate Representation for Optimizing Distributed Neural Networks

Keshav Santhanam, Siddharth Krishna, Ryota Tomioka, Andrew Fitzgibbon, Tim Harris

EuroMLSys '21: Proceedings of the 1st Workshop on Machine Learning and Systems | April 2021

Publication Github

On the Loss Landscape of Adversarial Training: Identifying Challenges and How to Overcome Them

Chen Liu, Mathieu Salzmann, Tao Lin, Ryota Tomioka, Sabine Süsstrunk

NeurIPS 2020 | December 2020

Publication

Conservative Uncertainty Estimation By Fitting Prior Networks

Kamil Ciosek, Vincent Fortuin, Ryota Tomioka, Katja Hofmann, Richard Turner

Eighth International Conference on Learning Representations (ICLR) | April 2020

Publication PDF Github Project Project

On Certifying Non-Uniform Bounds against Adversarial Attacks

Chen Liu, Ryota Tomioka, Volkan Cevher

International Conference on Machine Learning (ICML) | June 2019

Publication

Depth and nonlinearity induce implicit exploration for RL

Justas Dauparas, Ryota Tomioka, Katja Hofmann

ICML workshop on Exploration in RL | July 2018

Publication

Multi-Level Variational Autoencoder: Learning Disentangled Representations from Grouped Observations

Diane Bouchacourt, Ryota Tomioka, Sebastian Nowozin

AAAI 2018 | February 2018

Publication Project

QSGD: Communication-Efficient SGD via Gradient Quantization and Encoding

Dan Alistarh, Demjan Grubic, Jerry Li, Ryota Tomioka, Milan Vojnovic

Advances in Neural Information Processing Systems 30 (NIPS 2017) | December 2017

Publication

f-GAN: Training Generative Neural Samplers using Variational Divergence Minimization

Sebastian Nowozin, Botond Cseke, Ryota Tomioka

Advances in Neural Information Processing Systems 29 (NIPS 2016) | October 2016

Publication Publication Publication Project

Data-Dependent Path Normalization in Neural Networks

Behnam Neyshabur, Ryota Tomioka, Ruslan Salakhutdinov, Nathan Srebro

ICLR 2016 | November 2015

Publication

MatterGen: a generative model for inorganic materials design

Claudio Zeni, Robert Pinsler, Daniel Zügner, Andrew Fowler, Matthew Horton, Xiang Fu, Sasha Shysheya, Jonathan Crabbé, Lixin Sun, Jake Smith, Ryota Tomioka, Tian Xie

December 2023

PDF Publication Video Video Video Github

Gaussian Attention Model and Its Application to Knowledge Base Embedding and Question Answering

Liwen Zhang, John Winn, Ryota Tomioka

MSR-TR-2016-1141 | November 2016

Published by Microsoft

Publication