Ferenc Huszár

33 papers A* 3A 2Journal 25Unranked 3

Year	Rank	Type	Title / Venue / Authors
2025	A*	`conf`	Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning. ICLR Patrik Reizinger, Siyuan Guo, Ferenc Huszár, Bernhard Schölkopf, Wieland Brendel
2025	—	`conf`	In Which Areas of Technical AI Safety Could Geopolitical Rivals Cooperate? FAccT Ben Bucknall, Saad Siddiqui, Lara Thurnherr, Conor McGurk, Ben Harack, Anka Reuel, Patricia Paskov, Casey Mahoney, Sören Mindermann, Scott Singer, Vinay Hiremath, Charbel-Raphaël Ségerie, Oscar Delaney, Alessandro Abate, Fazl Barez, Michael K. Cohen, Philip Torr, Ferenc Huszár, Anisoara Calinescu, Gabriel Davis Jones, Robert Trager
2025	J	`jnl`	In Which Areas of Technical AI Safety Could Geopolitical Rivals Cooperate? CoRR Ben Bucknall, Saad Siddiqui, Lara Thurnherr, Conor McGurk, Ben Harack, Anka Reuel, Patricia Paskov, Casey Mahoney, Sören Mindermann, Scott Singer, Vinay Hiremath, Charbel-Raphaël Ségerie, Oscar Delaney, Alessandro Abate, Fazl Barez, Michael K. Cohen, Philip Torr, Ferenc Huszár, Anisoara Calinescu, Gabriel Davis Jones, Yoshua Bengio, Robert Trager
2025	J	`jnl`	Out-of-distribution Tests Reveal Compositionality in Chess Transformers. CoRR Anna Mészáros, Patrik Reizinger, Ferenc Huszár
2024	J	`jnl`	Beyond the Boundaries of Proximal Policy Optimization. CoRR Charlie B. Tan, Edan Toledo, Benjamin Ellis, Jakob N. Foerster, Ferenc Huszár
2024	J	`jnl`	Do Finetti: On Causal Effects for Exchangeable Data. CoRR Siyuan Guo, Chi Zhang, Karthika Mohan, Ferenc Huszár, Bernhard Schölkopf
2024	J	`jnl`	Identifiable Exchangeable Mechanisms for Causal Structure and Representation Learning. CoRR Patrik Reizinger, Siyuan Guo, Ferenc Huszár, Bernhard Schölkopf, Wieland Brendel
2024	J	`jnl`	Learning Beyond Pattern Matching? Assaying Mathematical Understanding in LLMs. CoRR Siyuan Guo, Aniket Didolkar, Nan Rosemary Ke, Anirudh Goyal, Ferenc Huszár, Bernhard Schölkopf
2024	A	`conf`	Meta-Learned Kernel For Blind Super-Resolution Kernel Estimation. WACV Royson Lee, Rui Li, Stylianos I. Venieris, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane
2024	A*	`conf`	Position: Understanding LLMs Requires More Than Statistical Generalization. ICML Patrik Reizinger, Szilvia Ujváry, Anna Mészáros, Anna Kerekes, Wieland Brendel, Ferenc Huszár
2024	A*	`conf`	Recurrent Early Exits for Federated Learning with Heterogeneous Clients. ICML Royson Lee, Javier Fernández-Marqués, Shell Xu Hu, Da Li, Stefanos Laskaridis, Lukasz Dudziak, Timothy M. Hospedales, Ferenc Huszár, Nicholas Donald Lane
2024	J	`jnl`	Recurrent Early Exits for Federated Learning with Heterogeneous Clients. CoRR Royson Lee, Javier Fernández-Marqués, Shell Xu Hu, Da Li, Stefanos Laskaridis, Lukasz Dudziak, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane
2024	J	`jnl`	Rule Extrapolation in Language Models: A Study of Compositional Generalization on OOD Prompts. CoRR Anna Mészáros, Szilvia Ujváry, Wieland Brendel, Patrik Reizinger, Ferenc Huszár
2024	J	`jnl`	Understanding LLMs Requires More Than Statistical Generalization. CoRR Patrik Reizinger, Szilvia Ujváry, Anna Mészáros, Anna Kerekes, Wieland Brendel, Ferenc Huszár
2023	J	`jnl`	FedL2P: Federated Learning to Personalize. CoRR Royson Lee, Minyoung Kim, Da Li, Xinchi Qiu, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane
2023	J	`jnl`	Jacobian-based Causal Discovery with Nonlinear ICA. Trans. Mach. Learn. Res. Patrik Reizinger, Yash Sharma, Matthias Bethge, Bernhard Schölkopf, Ferenc Huszár, Wieland Brendel
2023	J	`jnl`	Measuring disparate outcomes of content recommendation algorithms with distributional inequality metrics. Patterns Tomo Lazovich, Luca Belli, Aaron Gonzales, Amanda Bower, Uthaipon Tantipongpipat, Kristian Lum, Ferenc Huszár, Rumman Chowdhury
2022	J	`jnl`	Algorithmic amplification of politics on Twitter. Proc. Natl. Acad. Sci. USA Ferenc Huszár, Sofia Ira Ktena, Conor O'Brien, Luca Belli, Andrew Schlaikjer, Moritz Hardt
2022	J	`jnl`	Causal de Finetti: On the Identification of Invariant Causal Structure in Exchangeable Data. CoRR Siyuan Guo, Viktor Tóth, Bernhard Schölkopf, Ferenc Huszár
2022	J	`jnl`	Measuring disparate outcomes of content recommendation algorithms with distributional inequality metrics. Patterns Tomo Lazovich, Luca Belli, Aaron Gonzales, Amanda Bower, Uthaipon Tantipongpipat, Kristian Lum, Ferenc Huszár, Rumman Chowdhury
2022	J	`jnl`	Meta-Learned Kernel For Blind Super-Resolution Kernel Estimation. CoRR Royson Lee, Rui Li, Stylianos I. Venieris, Timothy M. Hospedales, Ferenc Huszár, Nicholas D. Lane
2022	J	`jnl`	Rethinking Sharpness-Aware Minimization as Variational Inference. CoRR Szilvia Ujváry, Zsigmond Telek, Anna Kerekes, Anna Mészáros, Ferenc Huszár
2021	J	`jnl`	Algorithmic Amplification of Politics on Twitter. CoRR Ferenc Huszár, Sofia Ira Ktena, Conor O'Brien, Luca Belli, Andrew Schlaikjer, Moritz Hardt
2021	J	`jnl`	Depth Without the Magic: Inductive Bias of Natural Gradient Descent. CoRR Anna Kerekes, Anna Mészáros, Ferenc Huszár
2019	A	`conf`	Addressing delayed feedback for continuous training with neural networks in CTR prediction. RecSys Sofia Ira Ktena, Alykhan Tejani, Lucas Theis, Pranay Kumar Myana, Deepak Dilipkumar, Ferenc Huszár, Steven Yoo, Wenzhe Shi
2018	J	`jnl`	Faster gaze prediction with dense networks and Fisher pruning. CoRR Lucas Theis, Iryna Korshunova, Alykhan Tejani, Ferenc Huszár
2017	—	`conf`	Amortised MAP Inference for Image Super-resolution. ICLR Casper Kaae Sønderby, Jose Caballero, Lucas Theis, Wenzhe Shi, Ferenc Huszár
2017	—	`conf`	Lossy Image Compression with Compressive Autoencoders. ICLR (Poster) Lucas Theis, Wenzhe Shi, Andrew Cunningham, Ferenc Huszár
2017	J	`jnl`	Lossy Image Compression with Compressive Autoencoders. CoRR Lucas Theis, Wenzhe Shi, Andrew Cunningham, Ferenc Huszár
2017	J	`jnl`	On Quadratic Penalties in Elastic Weight Consolidation. CoRR Ferenc Huszár
2017	J	`jnl`	Variational Inference using Implicit Distributions. CoRR Ferenc Huszár
2016	J	`jnl`	Amortised MAP Inference for Image Super-resolution. CoRR Casper Kaae Sønderby, Jose Caballero, Lucas Theis, Wenzhe Shi, Ferenc Huszár
2016	J	`jnl`	Real-Time Single Image and Video Super-Resolution Using an Efficient Sub-Pixel Convolutional Neural Network. CoRR Wenzhe Shi, Jose Caballero, Ferenc Huszár, Johannes Totz, Andrew P. Aitken, Rob Bishop, Daniel Rueckert, Zehan Wang