Ferenc Huszár

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 25

Top Topics

Lossy Image Compression

Convolutional Neural Network

Causal Structure

Variational Inference

Top Venues

Publications

Siyuan Guo, Aniket Didolkar, Nan Rosemary Ke, Anirudh Goyal, Ferenc Huszár, Bernhard Schölkopf
Learning Beyond Pattern Matching? Assaying Mathematical Understanding in LLMs. CoRR (2024)
Royson Lee, Rui Li, Stylianos I. Venieris, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane
Meta-Learned Kernel For Blind Super-Resolution Kernel Estimation. WACV (2024)
Royson Lee, Javier Fernández-Marqués, Shell Xu Hu, Da Li, Stefanos Laskaridis, Lukasz Dudziak, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane
Recurrent Early Exits for Federated Learning with Heterogeneous Clients. CoRR (2024)
Patrik Reizinger, Szilvia Ujváry, Anna Mészáros, Anna Kerekes, Wieland Brendel, Ferenc Huszár
Understanding LLMs Requires More Than Statistical Generalization. CoRR (2024)
Siyuan Guo, Chi Zhang, Karthika Mohan, Ferenc Huszár, Bernhard Schölkopf
Do Finetti: On Causal Effects for Exchangeable Data. CoRR (2024)
Patrik Reizinger, Siyuan Guo, Ferenc Huszár, Bernhard Schölkopf, Wieland Brendel
Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning. CoRR (2024)
Royson Lee, Minyoung Kim, Da Li, Xinchi Qiu, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane
FedL2P: Federated Learning to Personalize. CoRR (2023)
Patrik Reizinger, Yash Sharma, Matthias Bethge, Bernhard Schölkopf, Ferenc Huszár, Wieland Brendel
Jacobian-based Causal Discovery with Nonlinear ICA. Trans. Mach. Learn. Res. 2023 (2023)
Tomo Lazovich, Luca Belli, Aaron Gonzales, Amanda Bower, Uthaipon Tantipongpipat, Kristian Lum, Ferenc Huszár, Rumman Chowdhury
Measuring disparate outcomes of content recommendation algorithms with distributional inequality metrics. Patterns 4 (8) (2023)
Szilvia Ujváry, Zsigmond Telek, Anna Kerekes, Anna Mészáros, Ferenc Huszár
Rethinking Sharpness-Aware Minimization as Variational Inference. CoRR (2022)
Royson Lee, Rui Li, Stylianos I. Venieris, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane
Meta-Learned Kernel For Blind Super-Resolution Kernel Estimation. CoRR (2022)
Ferenc Huszár, Sofia Ira Ktena, Conor O'Brien, Luca Belli, Andrew Schlaikjer, Moritz Hardt
Algorithmic amplification of politics on Twitter. Proc. Natl. Acad. Sci. USA 119 (1) (2022)
Siyuan Guo, Viktor Tóth, Bernhard Schölkopf, Ferenc Huszár
Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data. CoRR (2022)
Tomo Lazovich, Luca Belli, Aaron Gonzales, Amanda Bower, Uthaipon Tantipongpipat, Kristian Lum, Ferenc Huszár, Rumman Chowdhury
Measuring disparate outcomes of content recommendation algorithms with distributional inequality metrics. Patterns 3 (8) (2022)
Ferenc Huszár, Sofia Ira Ktena, Conor O'Brien, Luca Belli, Andrew Schlaikjer, Moritz Hardt
Algorithmic Amplification of Politics on Twitter. CoRR (2021)
Anna Kerekes, Anna Mészáros, Ferenc Huszár
Depth Without the Magic: Inductive Bias of Natural Gradient Descent. CoRR (2021)
Sofia Ira Ktena, Alykhan Tejani, Lucas Theis, Pranay Kumar Myana, Deepak Dilipkumar, Ferenc Huszár, Steven Yoo, Wenzhe Shi
Addressing delayed feedback for continuous training with neural networks in CTR prediction. RecSys (2019)
Lucas Theis, Iryna Korshunova, Alykhan Tejani, Ferenc Huszár
Faster gaze prediction with dense networks and Fisher pruning. CoRR (2018)
Casper Kaae Sønderby, Jose Caballero, Lucas Theis, Wenzhe Shi, Ferenc Huszár
Amortised MAP Inference for Image Super-resolution. ICLR (2017)
Lucas Theis, Wenzhe Shi, Andrew Cunningham, Ferenc Huszár
Lossy Image Compression with Compressive Autoencoders. CoRR (2017)
Ferenc Huszár
Variational Inference using Implicit Distributions. CoRR (2017)
Ferenc Huszár
On Quadratic Penalties in Elastic Weight Consolidation. CoRR (2017)
Lucas Theis, Wenzhe Shi, Andrew Cunningham, Ferenc Huszár
Lossy Image Compression with Compressive Autoencoders. ICLR (Poster) (2017)
Casper Kaae Sønderby, Jose Caballero, Lucas Theis, Wenzhe Shi, Ferenc Huszár
Amortised MAP Inference for Image Super-resolution. CoRR (2016)
Wenzhe Shi, Jose Caballero, Ferenc Huszár, Johannes Totz, Andrew P. Aitken, Rob Bishop, Daniel Rueckert, Zehan Wang
Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network. CoRR (2016)