Ferenc Huszar

According to our database, Ferenc Huszar authored at least 31 papers between 2011 and 2024.

Collaborative distances:

• Dijkstra number of three.
• Erdős number of four.

2024

Meta-Learned Kernel For Blind Super-Resolution Kernel Estimation.

Royson Lee, Rui Li, Stylianos I. Venieris, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2024

2023

Measuring disparate outcomes of content recommendation algorithms with distributional inequality metrics.

Tomo Lazovich, Luca Belli, Aaron Gonzales, Amanda Bower, Uthaipon Tantipongpipat, Kristian Lum, Ferenc Huszár, Rumman Chowdhury

Patterns, August, 2023

nl-causal-representations.

Patrik Reizinger, Yash Sharma, Matthias Bethge, Bernhard Schölkopf, Ferenc Huszár, Wieland Brendel

Dataset, April, 2023

Jacobian-based Causal Discovery with Nonlinear ICA.

Patrik Reizinger, Yash Sharma, Matthias Bethge, Bernhard Schölkopf, Ferenc Huszár, Wieland Brendel

Trans. Mach. Learn. Res., 2023

FedL2P: Federated Learning to Personalize.

Royson Lee, Minyoung Kim, Da Li, Xinchi Qiu, Timothy M. Hospedales, Ferenc Huszar, Nicholas D. Lane

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data.

Siyuan Guo, Viktor Tóth, Bernhard Schölkopf, Ferenc Huszar

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

2022

nl-causal-representations.

Patrik Reizinger, Yash Sharma, Matthias Bethge, Bernhard Schölkopf, Ferenc Huszár, Wieland Brendel

Dataset, August, 2022

Algorithmic amplification of politics on Twitter.

Ferenc Huszár, Sofia Ira Ktena, Conor O'Brien, Luca Belli, Andrew Schlaikjer, Moritz Hardt

Proc. Natl. Acad. Sci. USA, 2022

Rethinking Sharpness-Aware Minimization as Variational Inference.

Szilvia Ujváry, Zsigmond Telek, Anna Kerekes, Anna Mészáros, Ferenc Huszár

CoRR, 2022

2021

Depth Without the Magic: Inductive Bias of Natural Gradient Descent.

Anna Kerekes, Anna Mészáros, Ferenc Huszár

CoRR, 2021

Efficient Wasserstein Natural Gradients for Reinforcement Learning.

Ted Moskovitz, Michael Arbel, Ferenc Huszar, Arthur Gretton

Proceedings of the 9th International Conference on Learning Representations, 2021

2020

Deep Bayesian Bandits: Exploring in Online Personalized Recommendations.

Dalin Guo, Sofia Ira Ktena, Ferenc Huszar, Pranay Kumar Myana, Wenzhe Shi, Alykhan Tejani

CoRR, 2020

Model Size Reduction Using Frequency Based Double Hashing for Recommender Systems.

Caojin Zhang, Yicun Liu, Yuanpu Xie, Sofia Ira Ktena, Alykhan Tejani, Akshay Gupta, Pranay Kumar Myana, Deepak Dilipkumar, Suvadip Paul, Ikuhiro Ihara, Prasang Upadhyaya, Ferenc Huszar, Wenzhe Shi

Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

Deep Bayesian Bandits: Exploring in Online Personalized Recommendations.

Dalin Guo, Sofia Ira Ktena, Pranay Kumar Myana, Ferenc Huszar, Wenzhe Shi, Alykhan Tejani, Michael Kneier, Sourav Das

Proceedings of the RecSys 2020: Fourteenth ACM Conference on Recommender Systems, 2020

2019

Addressing delayed feedback for continuous training with neural networks in CTR prediction.

Sofia Ira Ktena, Alykhan Tejani, Lucas Theis, Pranay Kumar Myana, Deepak Dilipkumar, Ferenc Huszár, Steven Yoo, Wenzhe Shi

Proceedings of the 13th ACM Conference on Recommender Systems, 2019

2018

Faster gaze prediction with dense networks and Fisher pruning.

Lucas Theis, Iryna Korshunova, Alykhan Tejani, Ferenc Huszár

CoRR, 2018

Adaptive Paired-Comparison Method for Subjective Video Quality Assessment on Mobile Devices.

Katherine Storrs, Sebastiaan Van Leuven, Steve Kojder, Lucas Theis, Ferenc Huszar

Proceedings of the 2018 Picture Coding Symposium, 2018

BRUNO: A Deep Recurrent Model for Exchangeable Data.

Iryna Korshunova, Jonas Degrave, Ferenc Huszar, Yarin Gal, Arthur Gretton, Joni Dambre

Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

2017

On Quadratic Penalties in Elastic Weight Consolidation.

Ferenc Huszár

CoRR, 2017

Variational Inference using Implicit Distributions.

Ferenc Huszár

CoRR, 2017

Lossy Image Compression with Compressive Autoencoders.

Lucas Theis, Wenzhe Shi, Andrew Cunningham, Ferenc Huszár

Proceedings of the 5th International Conference on Learning Representations, 2017

Amortised MAP Inference for Image Super-resolution.

Casper Kaae Sønderby, Jose Caballero, Lucas Theis, Wenzhe Shi, Ferenc Huszár

Proceedings of the 5th International Conference on Learning Representations, 2017

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network.

Christian Ledig, Lucas Theis, Ferenc Huszar, Jose Caballero, Andrew Cunningham, Alejandro Acosta, Andrew P. Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, Wenzhe Shi

Proceedings of the 2017 IEEE Conference on Computer Vision and Pattern Recognition, 2017

2016

Is the deconvolution layer the same as a convolutional layer?

Wenzhe Shi, Jose Caballero, Lucas Theis, Ferenc Huszar, Andrew P. Aitken, Christian Ledig, Zehan Wang

CoRR, 2016

Photo-Realistic Single Image Super-Resolution Using a Generative Adversarial Network.

Christian Ledig, Lucas Theis, Ferenc Huszar, Jose Caballero, Andrew P. Aitken, Alykhan Tejani, Johannes Totz, Zehan Wang, Wenzhe Shi

CoRR, 2016

Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network.

Wenzhe Shi, Jose Caballero, Ferenc Huszar, Johannes Totz, Andrew P. Aitken, Rob Bishop, Daniel Rueckert, Zehan Wang

Proceedings of the 2016 IEEE Conference on Computer Vision and Pattern Recognition, 2016

2015

How (not) to Train your Generative Model: Scheduled Sampling, Likelihood, Adversary?

Ferenc Huszar

CoRR, 2015

2012

Optimally-Weighted Herding is Bayesian Quadrature.

Ferenc Huszar, David Duvenaud

Proceedings of the Twenty-Eighth Conference on Uncertainty in Artificial Intelligence, 2012

Collaborative Gaussian Processes for Preference Learning.

Neil Houlsby, José Miguel Hernández-Lobato, Ferenc Huszar, Zoubin Ghahramani

Proceedings of the Advances in Neural Information Processing Systems 25: 26th Annual Conference on Neural Information Processing Systems 2012. Proceedings of a meeting held December 3-6, 2012

2011

Approximate inference for the loss-calibrated Bayesian.

Simon Lacoste-Julien, Ferenc Huszar, Zoubin Ghahramani

Proceedings of the Fourteenth International Conference on Artificial Intelligence and Statistics, 2011

Bayesian Active Learning for Classification and Preference Learning

Neil Houlsby, Ferenc Huszar, Zoubin Ghahramani, Máté Lengyel

CoRR, 2011