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Konstantinos Gourgoulias
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2020 – today
- 2024
- [j4]Kostis Gourgoulias, Najah Ghalyan, Maxime Labonne, Yash Satsangi, Sean Moran, Joseph Sabelja:
Estimating class separability of text embeddings with persistent homology. Trans. Mach. Learn. Res. 2024 (2024) - 2023
- [i10]Najah Ghalyan, Kostis Gourgoulias, Yash Satsangi, Sean Moran, Maxime Labonne, Joseph Sabelja:
An Unsupervised Method for Estimating Class Separability of Datasets with Application to LLMs Fine-Tuning. CoRR abs/2305.15016 (2023) - [i9]Jiaeli Shi, Najah Ghalyan, Kostis Gourgoulias, John Buford, Sean Moran:
DeepClean: Machine Unlearning on the Cheap by Resetting Privacy Sensitive Weights using the Fisher Diagonal. CoRR abs/2311.10448 (2023) - 2020
- [j3]Konstantinos Gourgoulias, Markos A. Katsoulakis, Luc Rey-Bellet, Jie Wang:
How Biased Is Your Model? Concentration Inequalities, Information and Model Bias. IEEE Trans. Inf. Theory 66(5): 3079-3097 (2020) - [i8]Divya Gautam, Maria Lomeli, Kostis Gourgoulias, Daniel H. Thompson, Saurabh Johri:
Masking schemes for universal marginalisers. CoRR abs/2001.05895 (2020) - [i7]Albert Buchard, Baptiste Bouvier, Giulia Prando, Rory Beard, Michail Livieratos, Dan Busbridge, Daniel H. Thompson, Jonathan G. Richens, Yuanzhao Zhang, Adam Baker, Yura Perov, Kostis Gourgoulias, Saurabh Johri:
Learning medical triage from clinicians using Deep Q-Learning. CoRR abs/2003.12828 (2020)
2010 – 2019
- 2019
- [c1]Yura Perov, Logan Graham, Kostis Gourgoulias, Jonathan G. Richens, Ciarán M. Lee, Adam Baker, Saurabh Johri:
MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming. AABI 2019: 1-36 - [i6]Robert Walecki, Kostis Gourgoulias, Adam Baker, Chris Hart, Chris Lucas, Max Zwiessele, Albert Buchard, Maria Lomeli, Yura Perov, Saurabh Johri:
Universal Marginaliser for Deep Amortised Inference for Probabilistic Programs. CoRR abs/1910.07474 (2019) - [i5]Yura Perov, Logan Graham, Kostis Gourgoulias, Jonathan G. Richens, Ciarán M. Lee, Adam Baker, Saurabh Johri:
MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming. CoRR abs/1910.08091 (2019) - 2018
- [i4]Robert Walecki, Albert Buchard, Kostis Gourgoulias, Chris Hart, Maria Lomeli, Alexandre K. W. Navarro, Max Zwiessele, Yura Perov, Saurabh Johri:
Universal Marginalizer for Amortised Inference and Embedding of Generative Models. CoRR abs/1811.04727 (2018) - 2017
- [j2]Konstantinos Gourgoulias, Markos A. Katsoulakis, Luc Rey-Bellet:
Information criteria for quantifying loss of reversibility in parallelized KMC. J. Comput. Phys. 328: 438-454 (2017) - [i3]Konstantinos Gourgoulias, Markos A. Katsoulakis, Luc Rey-Bellet, Jie Wang:
How biased is your model? Concentration Inequalities, Information and Model Bias. CoRR abs/1706.10260 (2017) - [i2]Laura Douglas, Iliyan Zarov, Konstantinos Gourgoulias, Chris Lucas, Chris Hart, Adam Baker, Maneesh Sahani, Yura Perov, Saurabh Johri:
A Universal Marginalizer for Amortized Inference in Generative Models. CoRR abs/1711.00695 (2017) - 2016
- [j1]Konstantinos Gourgoulias, Markos A. Katsoulakis, Luc Rey-Bellet:
Information Metrics For Long-Time Errors in Splitting Schemes For Stochastic Dynamics and Parallel Kinetic Monte Carlo. SIAM J. Sci. Comput. 38(6) (2016) - [i1]Konstantinos Gourgoulias, Markos A. Katsoulakis, Luc Rey-Bellet:
Information Criteria for quantifying loss of reversibility in parallelized KMC. CoRR abs/1605.02375 (2016)
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last updated on 2024-08-10 00:25 CEST by the dblp team
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