Francisco J. R. Ruiz

Publication Activity (10 Years)

Years Active: 2011-2024
Publications (10 Years): 41

Top Topics

Gaussian Process

Variational Inference

Channel Estimation

Top Venues

Publications

Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Matej Balog, M. Pawan Kumar, Emilien Dupont, Francisco J. R. Ruiz, Jordan S. Ellenberg, Pengming Wang, Omar Fawzi, Pushmeet Kohli, Alhussein Fawzi
Mathematical discoveries from program search with large language models. Nat. 625 (7995) (2024)
Francisco J. R. Ruiz, Tuomas Laakkonen, Johannes Bausch, Matej Balog, Mohammadamin Barekatain, Francisco J. H. Heras, Alexander Novikov, Nathan Fitzpatrick, Bernardino Romera-Paredes, John van de Wetering, Alhussein Fawzi, Konstantinos Meichanetzidis, Pushmeet Kohli
Quantum Circuit Optimization with AlphaTensor. CoRR (2024)
Virginia Aglietti, Ira Ktena, Jessica Schrouff, Eleni Sgouritsa, Francisco J. R. Ruiz, Alan Malek, Alexis Bellot, Silvia Chiappa
FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch. CoRR (2024)
Xu Han, Xiaohui Chen, Francisco J. R. Ruiz, Li-Ping Liu
Fitting Autoregressive Graph Generative Models through Maximum Likelihood Estimation. J. Mach. Learn. Res. 24 (2023)
Alhussein Fawzi, Matej Balog, Aja Huang, Thomas Hubert, Bernardino Romera-Paredes, Mohammadamin Barekatain, Alexander Novikov, Francisco J. R. Ruiz, Julian Schrittwieser, Grzegorz Swirszcz, David Silver, Demis Hassabis, Pushmeet Kohli
Discovering faster matrix multiplication algorithms with reinforcement learning. Nat. 610 (7930) (2022)
Francisco J. R. Ruiz, Michalis K. Titsias, A. Taylan Cemgil, Arnaud Doucet
Unbiased gradient estimation for variational auto-encoders using coupled Markov chains. UAI (2021)
Xiaohui Chen, Xu Han, Jiajing Hu, Francisco J. R. Ruiz, Li-Ping Liu
Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation. ICML (2021)
Michalis K. Titsias, Francisco J. R. Ruiz, Sotirios Nikoloutsopoulos, Alexandre Galashov
Information theoretic meta learning with Gaussian processes. UAI (2021)
Xiaohui Chen, Xu Han, Jiajing Hu, Francisco J. R. Ruiz, Li-Ping Liu
Order Matters: Probabilistic Modeling of Node Sequence for Graph Generation. CoRR (2021)
Lorenz Richter, Ayman Boustati, Nikolas Nüsken, Francisco J. R. Ruiz, Ömer Deniz Akyildiz
VarGrad: A Low-Variance Gradient Estimator for Variational Inference. NeurIPS (2020)
Francisco J. R. Ruiz, Michalis K. Titsias, A. Taylan Cemgil, Arnaud Doucet
Unbiased Gradient Estimation for Variational Auto-Encoders using Coupled Markov Chains. CoRR (2020)
Lorenz Richter, Ayman Boustati, Nikolas Nüsken, Francisco J. R. Ruiz, Ömer Deniz Akyildiz
VarGrad: A Low-Variance Gradient Estimator for Variational Inference. CoRR (2020)
Adji Bousso Dieng, Francisco J. R. Ruiz, David M. Blei
Topic Modeling in Embedding Spaces. Trans. Assoc. Comput. Linguistics 8 (2020)
Adji B. Dieng, Francisco J. R. Ruiz, David M. Blei
The Dynamic Embedded Topic Model. CoRR (2019)
Adji B. Dieng, Francisco J. R. Ruiz, David M. Blei, Michalis K. Titsias
Prescribed Generative Adversarial Networks. CoRR (2019)
Michalis K. Titsias, Francisco J. R. Ruiz
Unbiased Implicit Variational Inference. AISTATS (2019)
Francisco J. R. Ruiz, Michalis K. Titsias
A Contrastive Divergence for Combining Variational Inference and MCMC. CoRR (2019)
Robert Donnelly, Francisco J. R. Ruiz, David M. Blei, Susan Athey
Counterfactual Inference for Consumer Choice Across Many Product Categories. CoRR (2019)
Adji B. Dieng, Francisco J. R. Ruiz, David M. Blei
Topic Modeling in Embedding Spaces. CoRR (2019)
Francisco J. R. Ruiz, Michalis K. Titsias
A Contrastive Divergence for Combining Variational Inference and MCMC. ICML (2019)
Michalis K. Titsias, Francisco J. R. Ruiz
Unbiased Implicit Variational Inference. CoRR (2018)
Francisco J. R. Ruiz, Michalis K. Titsias, Adji B. Dieng, David M. Blei
Augment and Reduce: Stochastic Inference for Large Categorical Distributions. ICML (2018)
Francisco J. R. Ruiz, Isabel Valera, Lennart Svensson, Fernando Pérez-Cruz
Infinite Factorial Finite State Machine for Blind Multiuser Channel Estimation. IEEE Trans. Cogn. Commun. Netw. 4 (2) (2018)
Susan Athey, David M. Blei, Robert Donnelly, Francisco J. R. Ruiz, Tobias Schmidt
Estimating Heterogeneous Consumer Preferences for Restaurants and Travel Time Using Mobile Location Data. CoRR (2018)
Francisco J. R. Ruiz, Michalis K. Titsias, Adji B. Dieng, David M. Blei
Augment and Reduce: Stochastic Inference for Large Categorical Distributions. CoRR (2018)
Maryam Fatemi, Karl Granström, Lennart Svensson, Francisco J. R. Ruiz, Lars Hammarstrand
Poisson Multi-Bernoulli Mapping Using Gibbs Sampling. CoRR (2018)
Francisco J. R. Ruiz, Isabel Valera, Lennart Svensson, Fernando Pérez-Cruz
Infinite Factorial Finite State Machine for Blind Multiuser Channel Estimation. CoRR (2018)
Francisco J. R. Ruiz, Susan Athey, David M. Blei
SHOPPER: A Probabilistic Model of Consumer Choice with Substitutes and Complements. CoRR (2017)
Li-Ping Liu, Francisco J. R. Ruiz, Susan Athey, David M. Blei
Context Selection for Embedding Models. NIPS (2017)
Maja Rudolph, Francisco J. R. Ruiz, Susan Athey, David M. Blei
Structured Embedding Models for Grouped Data. CoRR (2017)
Maryam Fatemi, Karl Granström, Lennart Svensson, Francisco J. R. Ruiz, Lars Hammarstrand
Poisson Multi-Bernoulli Mapping Using Gibbs Sampling. IEEE Trans. Signal Process. 65 (11) (2017)
Maja Rudolph, Francisco J. R. Ruiz, Susan Athey, David M. Blei
Structured Embedding Models for Grouped Data. NIPS (2017)
Christian A. Naesseth, Francisco J. R. Ruiz, Scott W. Linderman, David M. Blei
Reparameterization Gradients through Acceptance-Rejection Sampling Algorithms. AISTATS (2017)
Francisco J. R. Ruiz, Michalis K. Titsias, David M. Blei
The Generalized Reparameterization Gradient. NIPS (2016)
Francisco J. R. Ruiz, Michalis K. Titsias, David M. Blei
Overdispersed Black-Box Variational Inference. UAI (2016)
Maja Rudolph, Francisco J. R. Ruiz, Stephan Mandt, David M. Blei
Exponential Family Embeddings. CoRR (2016)
Maja Rudolph, Francisco J. R. Ruiz, Stephan Mandt, David M. Blei
Exponential Family Embeddings. NIPS (2016)
Isabel Valera, Francisco J. R. Ruiz, Fernando Pérez-Cruz
Infinite Factorial Unbounded-State Hidden Markov Model. IEEE Trans. Pattern Anal. Mach. Intell. 38 (9) (2016)
Isabel Valera, Francisco J. R. Ruiz, Pablo M. Olmos, Carlos Blanco, Fernando Pérez-Cruz
Infinite Continuous Feature Model for Psychiatric Comorbidity Analysis. Neural Comput. 28 (2) (2016)
Isabel Valera, Francisco J. R. Ruiz, Lennart Svensson, Fernando Pérez-Cruz
Infinite Factorial Dynamical Model. NIPS (2015)
Isabel Valera, Francisco J. R. Ruiz, Lennart Svensson, Fernando Pérez-Cruz
A Bayesian nonparametric approach for blind multiuser channel estimation. EUSIPCO (2015)
Francisco J. R. Ruiz, Isabel Valera, Carlos Blanco, Fernando Pérez-Cruz
Bayesian nonparametric comorbidity analysis of psychiatric disorders. J. Mach. Learn. Res. 15 (1) (2014)
Prem Gopalan, Francisco J. R. Ruiz, Rajesh Ranganath, David M. Blei
Bayesian Nonparametric Poisson Factorization for Recommendation Systems. AISTATS (2014)
Francisco J. R. Ruiz, Isabel Valera, Carlos Blanco, Fernando Pérez-Cruz
Bayesian nonparametric comorbidity analysis of psychiatric disorders. CoRR (2014)
Isabel Valera, Francisco J. R. Ruiz, Fernando Pérez-Cruz
Sinfinite factorial unbounded hidden Markov model for blind multiuser channel estimation. CIP (2014)
Francisco J. R. Ruiz, Isabel Valera, Carlos Blanco, Fernando Pérez-Cruz
Bayesian Nonparametric Modeling of Suicide Attempts. NIPS (2012)
Francisco J. R. Ruiz, Fernando Pérez-Cruz
Zero-error codes for the noisy-typewriter channel. ITW (2011)