Marton Havasi

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 17

Top Topics

Stochastic Gradient

Top Venues

IEEE Comput. Archit. Lett.

Publications

Buu Phan, Marton Havasi, Matthew J. Muckley, Karen Ullrich
Understanding and Mitigating Tokenization Bias in Language Models. CoRR (2024)
Marton Havasi, Sonali Parbhoo, Finale Doshi-Velez
Guarantee Regions for Local Explanations. CoRR (2024)
Marton Havasi, Sonali Parbhoo, Finale Doshi-Velez
Addressing Leakage in Concept Bottleneck Models. NeurIPS (2022)
Zixi Chen, Varshini Subhash, Marton Havasi, Weiwei Pan, Finale Doshi-Velez
Does the explanation satisfy your needs?: A unified view of properties of explanations. CoRR (2022)
Carissa Wu, Sonali Parbhoo, Marton Havasi, Finale Doshi-Velez
Learning Optimal Summaries of Clinical Time-series with Concept Bottleneck Models. MLHC (2022)
Marton Havasi, Jasper Snoek, Dustin Tran, Jonathan Gordon, José Miguel Hernández-Lobato
Sampling the Variational Posterior with Local Refinement. Entropy 23 (11) (2021)
Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew Mingbo Dai, Dustin Tran
Training independent subnetworks for robust prediction. ICLR (2021)
Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Liu, Zelda Mariet, Jeremy Nixon, Shreyas Padhy, Jie Ren, Tim G. J. Rudner, Yeming Wen, Florian Wenzel, Kevin Murphy, D. Sculley, Balaji Lakshminarayanan, Jasper Snoek, Yarin Gal, Dustin Tran
Uncertainty Baselines: Benchmarks for Uncertainty & Robustness in Deep Learning. CoRR (2021)
Marton Havasi, Rodolphe Jenatton, Stanislav Fort, Jeremiah Zhe Liu, Jasper Snoek, Balaji Lakshminarayanan, Andrew M. Dai, Dustin Tran
Training independent subnetworks for robust prediction. CoRR (2020)
Gergely Flamich, Marton Havasi, José Miguel Hernández-Lobato
Compressing Images by Encoding Their Latent Representations with Relative Entropy Coding. CoRR (2020)
Kshitij Bhardwaj, Marton Havasi, Yuan Yao, David M. Brooks, José Miguel Hernández-Lobato, Gu-Yeon Wei
A comprehensive methodology to determine optimal coherence interfaces for many-accelerator SoCs. ISLPED (2020)
Gergely Flamich, Marton Havasi, José Miguel Hernández-Lobato
Compressing Images by Encoding Their Latent Representations with Relative Entropy Coding. NeurIPS (2020)
Marton Havasi, Robert Peharz, José Miguel Hernández-Lobato
Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters. ICLR (Poster) (2019)
Kshitij Bhardwaj, Marton Havasi, Yuan Yao, David M. Brooks, José Miguel Hernández-Lobato, Gu-Yeon Wei
Determining Optimal Coherency Interface for Many-Accelerator SoCs Using Bayesian Optimization. IEEE Comput. Archit. Lett. 18 (2) (2019)
Marton Havasi, Robert Peharz, José Miguel Hernández-Lobato
Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters. CoRR (2018)
Marton Havasi, José Miguel Hernández-Lobato, Juan José Murillo-Fuentes
Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo. CoRR (2018)
Marton Havasi, José Miguel Hernández-Lobato, Juan José Murillo-Fuentes
Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo. NeurIPS (2018)