Konstantinos Gourgoulias

According to our database, Konstantinos Gourgoulias authored at least 12 papers between 2016 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of four.

2024

Estimating class separability of text embeddings with persistent homology.

Kostis Gourgoulias, Najah Ghalyan, Maxime Labonne, Yash Satsangi, Sean Moran, Joseph Sabelja

Trans. Mach. Learn. Res., 2024

2023

DeepClean: Machine Unlearning on the Cheap by Resetting Privacy Sensitive Weights using the Fisher Diagonal.

Jiaeli Shi, Najah Ghalyan, Kostis Gourgoulias, John Buford, Sean Moran

CoRR, 2023

An Unsupervised Method for Estimating Class Separability of Datasets with Application to LLMs Fine-Tuning.

Najah Ghalyan, Kostis Gourgoulias, Yash Satsangi, Sean Moran, Maxime Labonne, Joseph Sabelja

CoRR, 2023

2020

How Biased Is Your Model? Concentration Inequalities, Information and Model Bias.

Konstantinos Gourgoulias, Markos A. Katsoulakis, Luc Rey-Bellet, Jie Wang

IEEE Trans. Inf. Theory, 2020

Learning medical triage from clinicians using Deep Q-Learning.

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

CoRR, 2020

Masking schemes for universal marginalisers.

Divya Gautam, Maria Lomeli, Kostis Gourgoulias, Daniel H. Thompson, Saurabh Johri

CoRR, 2020

2019

Universal Marginaliser for Deep Amortised Inference for Probabilistic Programs.

Robert Walecki, Kostis Gourgoulias, Adam Baker, Chris Hart, Chris Lucas, Max Zwiessele, Albert Buchard, Maria Lomeli, Yura Perov, Saurabh Johri

CoRR, 2019

MultiVerse: Causal Reasoning using Importance Sampling in Probabilistic Programming.

Yura Perov, Logan Graham, Kostis Gourgoulias, Jonathan G. Richens, Ciarán M. Lee, Adam Baker, Saurabh Johri

Proceedings of the Symposium on Advances in Approximate Bayesian Inference, 2019

2018

Universal Marginalizer for Amortised Inference and Embedding of Generative Models.

Robert Walecki, Albert Buchard, Kostis Gourgoulias, Chris Hart, Maria Lomeli, Alexandre K. W. Navarro, Max Zwiessele, Yura Perov, Saurabh Johri

CoRR, 2018

2017

Information criteria for quantifying loss of reversibility in parallelized KMC.

Konstantinos Gourgoulias, Markos A. Katsoulakis, Luc Rey-Bellet

J. Comput. Phys., 2017

A Universal Marginalizer for Amortized Inference in Generative Models.

Laura Douglas, Iliyan Zarov, Konstantinos Gourgoulias, Chris Lucas, Chris Hart, Adam Baker, Maneesh Sahani, Yura Perov, Saurabh Johri

CoRR, 2017

2016

Information Metrics For Long-Time Errors in Splitting Schemes For Stochastic Dynamics and Parallel Kinetic Monte Carlo.

Konstantinos Gourgoulias, Markos A. Katsoulakis, Luc Rey-Bellet

SIAM J. Sci. Comput., 2016