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2020 – today
- 2024
[i8]Marton Havasi, Sonali Parbhoo, Finale Doshi-Velez:
Guarantee Regions for Local Explanations. CoRR abs/2402.12737 (2024)- [i7]Buu Phan, Marton Havasi, Matthew J. Muckley, Karen Ullrich:
Understanding and Mitigating Tokenization Bias in Language Models. CoRR abs/2406.16829 (2024) - 2022
- [c7]Carissa Wu, Sonali Parbhoo, Marton Havasi, Finale Doshi-Velez:
Learning Optimal Summaries of Clinical Time-series with Concept Bottleneck Models. MLHC 2022: 648-672 - [c6]Marton Havasi, Sonali Parbhoo, Finale Doshi-Velez:
Addressing Leakage in Concept Bottleneck Models. NeurIPS 2022 - [i6]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 abs/2211.05667 (2022) - 2021
- [j2]Marton Havasi, Jasper Snoek, Dustin Tran, Jonathan Gordon, José Miguel Hernández-Lobato:
Sampling the Variational Posterior with Local Refinement. Entropy 23(11): 1475 (2021) - [c5]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 - [i5]Zachary Nado, Neil Band, Mark Collier, Josip Djolonga, Michael W. Dusenberry, Sebastian Farquhar, Angelos Filos, Marton Havasi, Rodolphe Jenatton, Ghassen Jerfel, Jeremiah Z. 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 abs/2106.04015 (2021) - 2020
- [c4]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: 145-150 - [c3]Gergely Flamich, Marton Havasi, José Miguel Hernández-Lobato:
Compressing Images by Encoding Their Latent Representations with Relative Entropy Coding. NeurIPS 2020 - [i4]Gergely Flamich, Marton Havasi, José Miguel Hernández-Lobato:
Compressing Images by Encoding Their Latent Representations with Relative Entropy Coding. CoRR abs/2010.01185 (2020) - [i3]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 abs/2010.06610 (2020)
2010 – 2019
- 2019
- [j1]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): 119-123 (2019) - [c2]Marton Havasi, Robert Peharz, José Miguel Hernández-Lobato:
Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters. ICLR (Poster) 2019 - 2018
- [c1]Marton Havasi, José Miguel Hernández-Lobato, Juan José Murillo-Fuentes:
Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo. NeurIPS 2018: 7517-7527 - [i2]Marton Havasi, José Miguel Hernández-Lobato, Juan José Murillo-Fuentes:
Inference in Deep Gaussian Processes using Stochastic Gradient Hamiltonian Monte Carlo. CoRR abs/1806.05490 (2018) - [i1]Marton Havasi, Robert Peharz, José Miguel Hernández-Lobato:
Minimal Random Code Learning: Getting Bits Back from Compressed Model Parameters. CoRR abs/1810.00440 (2018)
Coauthor Index
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