Paul K. Rubenstein

24 papers A* 2A 5C 1Journal 13Unranked 2

Year	Rank	Type	Title / Venue / Authors
2023	J	`jnl`	AudioPaLM: A Large Language Model That Can Speak and Listen. CoRR 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
2023	J	`jnl`	Learning Translation Quality Evaluation on Low Resource Languages from Large Language Models. CoRR Amirkeivan Mohtashami, Mauro Verzetti, Paul K. Rubenstein
2023	C	`conf`	SLM: Bridge the Thin Gap Between Speech and Text Foundation Models. ASRU 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
2023	J	`jnl`	SLM: Bridge the thin gap between speech and text foundation models. CoRR 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
2023	A	`conf`	Spatial Consistency Loss for Training Multi-Label Classifiers from Single-Label Annotations. WACV Thomas Verelst, Paul K. Rubenstein, Marcin Eichner, Tinne Tuytelaars, Maxim Berman
2022	J	`jnl`	Spatial Consistency Loss for Training Multi-Label Classifiers from Single-Label Annotations. CoRR Thomas Verelst, Paul K. Rubenstein, Marcin Eichner, Tinne Tuytelaars, Maxim Berman
2020	—	`—`	Advances in latent variable and causal models Paul K. Rubenstein
2020	A*	`conf`	On Mutual Information Maximization for Representation Learning. ICLR Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic
2019	J	`jnl`	On Mutual Information Maximization for Representation Learning. CoRR Michael Tschannen, Josip Djolonga, Paul K. Rubenstein, Sylvain Gelly, Mario Lucic
2019	J	`jnl`	Optimal experimental design via Bayesian optimization: active causal structure learning for Gaussian process networks. CoRR Julius von Kügelgen, Paul K. Rubenstein, Bernhard Schölkopf, Adrian Weller
2019	A*	`conf`	Practical and Consistent Estimation of f-Divergences. NeurIPS Paul K. Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya O. Tolstikhin
2019	J	`jnl`	Practical and Consistent Estimation of f-Divergences. CoRR Paul K. Rubenstein, Olivier Bousquet, Josip Djolonga, Carlos Riquelme, Ilya O. Tolstikhin
2019	J	`jnl`	The Incomplete Rosetta Stone Problem: Identifiability Results for Multi-View Nonlinear ICA. CoRR Luigi Gresele, Paul K. Rubenstein, Arash Mehrjou, Francesco Locatello, Bernhard Schölkopf
2019	A	`conf`	The Incomplete Rosetta Stone problem: Identifiability results for Multi-view Nonlinear ICA. UAI Luigi Gresele, Paul K. Rubenstein, Arash Mehrjou, Francesco Locatello, Bernhard Schölkopf
2018	J	`jnl`	An Empirical Study of Generative Models with Encoders. CoRR Paul K. Rubenstein, Yunpeng Li, Dominik Roblek
2018	A	`conf`	From Deterministic ODEs to Dynamic Structural Causal Models. UAI Paul K. Rubenstein, Stephan Bongers, Joris M. Mooij, Bernhard Schölkopf
2018	—	`conf`	Learning Disentangled Representations with Wasserstein Auto-Encoders. ICLR (Workshop) Paul K. Rubenstein, Bernhard Schölkopf, Ilya O. Tolstikhin
2018	J	`jnl`	On the Latent Space of Wasserstein Auto-Encoders. CoRR Paul K. Rubenstein, Bernhard Schölkopf, Ilya O. Tolstikhin
2018	—	`conf`	Wasserstein Auto-Encoders: Latent Dimensionality and Random Encoders. ICLR (Workshop) Paul K. Rubenstein, Bernhard Schölkopf, Ilya O. Tolstikhin
2017	A	`conf`	Causal Consistency of Structural Equation Models. UAI Paul K. Rubenstein, Sebastian Weichwald, Stephan Bongers, Joris M. Mooij, Dominik Janzing, Moritz Grosse-Wentrup, Bernhard Schölkopf
2017	J	`jnl`	Causal Consistency of Structural Equation Models. CoRR Paul K. Rubenstein, Sebastian Weichwald, Stephan Bongers, Joris M. Mooij, Dominik Janzing, Moritz Grosse-Wentrup, Bernhard Schölkopf
2017	J	`jnl`	Probabilistic Active Learning of Functions in Structural Causal Models. CoRR Paul K. Rubenstein, Ilya O. Tolstikhin, Philipp Hennig, Bernhard Schölkopf
2016	A	`conf`	A Kernel Test for Three-Variable Interactions with Random Processes. UAI Paul K. Rubenstein, Kacper Chwialkowski, Arthur Gretton
2016	J	`jnl`	From Deterministic ODEs to Dynamic Structural Causal Models. CoRR Paul K. Rubenstein, Stephan Bongers, Joris M. Mooij, Bernhard Schölkopf