Paul K. Rubenstein

Publication Activity (10 Years)

Years Active: 2016-2023
Publications (10 Years): 23

Top Topics

Causal Relations

Structural Equation Models

Top Venues

ICLR (Workshop)

Publications

Mingqiu Wang, Wei Han, Izhak Shafran, Zelin Wu, Chung-Cheng Chiu, Yuan Cao, Yongqiang Wang, Nanxin Chen, Yu Zhang, Hagen Soltau, Paul K. Rubenstein, Lukas Zilka, Dian Yu, Zhong Meng, Golan Pundak, Nikhil Siddhartha, Johan Schalkwyk, Yonghui Wu
SLM: Bridge the thin gap between speech and text foundation models. CoRR (2023)
Amirkeivan Mohtashami, Mauro Verzetti, Paul K. Rubenstein
Learning Translation Quality Evaluation on Low Resource Languages from Large Language Models. CoRR (2023)
Paul K. Rubenstein, Chulayuth Asawaroengchai, Duc Dung Nguyen, Ankur Bapna, Zalán Borsos, Félix de Chaumont Quitry, Peter Chen, Dalia El Badawy, Wei Han, Eugene Kharitonov, Hannah Muckenhirn, Dirk Padfield, James Qin, Danny Rozenberg, Tara N. Sainath, Johan Schalkwyk, Matthew Sharifi, Michelle Tadmor Ramanovich, Marco Tagliasacchi, Alexandru Tudor, Mihajlo Velimirovic, Damien Vincent, Jiahui Yu, Yongqiang Wang, Vicky Zayats, Neil Zeghidour, Yu Zhang, Zhishuai Zhang, Lukas Zilka, Christian Havnø Frank
AudioPaLM: A Large Language Model That Can Speak and Listen. CoRR (2023)
Mingqiu Wang, Wei Han, Izhak Shafran, Zelin Wu, Chung-Cheng Chiu, Yuan Cao, Nanxin Chen, Yu Zhang, Hagen Soltau, Paul K. Rubenstein, Lukas Zilka, Dian Yu, Golan Pundak, Nikhil Siddhartha, Johan Schalkwyk, Yonghui Wu
SLM: Bridge the Thin Gap Between Speech and Text Foundation Models. ASRU (2023)
Thomas Verelst, Paul K. Rubenstein, Marcin Eichner, Tinne Tuytelaars, Maxim Berman
Spatial Consistency Loss for Training Multi-Label Classifiers from Single-Label Annotations. WACV (2023)
Thomas Verelst, Paul K. Rubenstein, Marcin Eichner, Tinne Tuytelaars, Maxim Berman
Spatial Consistency Loss for Training Multi-Label Classifiers from Single-Label Annotations. CoRR (2022)
Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic
On Mutual Information Maximization for Representation Learning. ICLR (2020)
Paul K. Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya O. Tolstikhin
Practical and Consistent Estimation of f-Divergences. NeurIPS (2019)
Luigi Gresele, Paul K. Rubenstein, Arash Mehrjou, Francesco Locatello, Bernhard Schölkopf
The Incomplete Rosetta Stone Problem: Identifiability Results for Multi-View Nonlinear ICA. CoRR (2019)
Luigi Gresele, Paul K. Rubenstein, Arash Mehrjou, Francesco Locatello, Bernhard Schölkopf
The Incomplete Rosetta Stone problem: Identifiability results for Multi-view Nonlinear ICA. UAI (2019)
Paul K. Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya O. Tolstikhin
Practical and Consistent Estimation of f-Divergences. CoRR (2019)
Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic
On Mutual Information Maximization for Representation Learning. CoRR (2019)
Julius von Kügelgen, Paul K. Rubenstein, Bernhard Schölkopf, Adrian Weller
Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks. CoRR (2019)
Paul K. Rubenstein, Stephan Bongers, Joris M. Mooij, Bernhard Schölkopf
From Deterministic ODEs to Dynamic Structural Causal Models. UAI (2018)
Paul K. Rubenstein, Yunpeng Li, Dominik Roblek
An Empirical Study of Generative Models with Encoders. CoRR (2018)
Paul K. Rubenstein, Bernhard Schölkopf, Ilya O. Tolstikhin
Wasserstein Auto-Encoders: Latent Dimensionality and Random Encoders. ICLR (Workshop) (2018)
Paul K. Rubenstein, Bernhard Schölkopf, Ilya O. Tolstikhin
On the Latent Space of Wasserstein Auto-Encoders. CoRR (2018)
Paul K. Rubenstein, Bernhard Schölkopf, Ilya O. Tolstikhin
Learning Disentangled Representations with Wasserstein Auto-Encoders. ICLR (Workshop) (2018)
Paul K. Rubenstein, Sebastian Weichwald, Stephan Bongers, Joris M. Mooij, Dominik Janzing, Moritz Grosse-Wentrup, Bernhard Schölkopf
Causal Consistency of Structural Equation Models. CoRR (2017)
Paul K. Rubenstein, Sebastian Weichwald, Stephan Bongers, Joris M. Mooij, Dominik Janzing, Moritz Grosse-Wentrup, Bernhard Schölkopf
Causal Consistency of Structural Equation Models. UAI (2017)
Paul K. Rubenstein, Ilya O. Tolstikhin, Philipp Hennig, Bernhard Schölkopf
Probabilistic Active Learning of Functions in Structural Causal Models. CoRR (2017)
Paul K. Rubenstein, Kacper Chwialkowski, Arthur Gretton
A Kernel Test for Three-Variable Interactions with Random Processes. UAI (2016)
Paul K. Rubenstein, Stephan Bongers, Joris M. Mooij, Bernhard Schölkopf
From Deterministic ODEs to Dynamic Structural Causal Models. CoRR (2016)