Argument Extraction from News, Blogs, and Social Media. - Theodosios Goudas; Christos Louizos; Georgios Petasis; Vangelis Karkaletsis (SETN, 2014)

Argument Extraction from News, Blogs, and the Social Web. - Theodosios Goudas; Christos Louizos; Georgios Petasis; Vangelis Karkaletsis (Int. J. Artif. Intell. Tools, 2015)

Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors. - Christos Louizos; Max Welling (ICML, 2016)

The Variational Fair Autoencoder. - Christos Louizos; Kevin Swersky; Yujia Li 001; Max Welling; Richard S. Zemel (ICLR, 2016)

Multiplicative Normalizing Flows for Variational Bayesian Neural Networks. - Christos Louizos; Max Welling (ICML, 2017)

Causal Effect Inference with Deep Latent-Variable Models. - Christos Louizos; Uri Shalit; Joris M. Mooij; David A. Sontag; Richard S. Zemel; Max Welling (NIPS, 2017)

Bayesian Compression for Deep Learning. - Christos Louizos; Karen Ullrich; Max Welling (NIPS, 2017)

Learning Sparse Neural Networks through L0 Regularization. - Christos Louizos; Max Welling; Diederik P. Kingma (CoRR, 2017)

Learning Sparse Neural Networks through L_0 Regularization. - Christos Louizos; Max Welling; Diederik P. Kingma (ICLR (Poster), 2018)

DIVA: Domain Invariant Variational Autoencoder. - Maximilian Ilse; Jakub M. Tomczak; Christos Louizos; Max Welling (DGS@ICLR, 2019)

Relaxed Quantization for Discretized Neural Networks. - Christos Louizos; Matthias Reisser; Tijmen Blankevoort; Efstratios Gavves; Max Welling (ICLR (Poster), 2019)

The Functional Neural Process. - Christos Louizos; Xiahan Shi; Klamer Schutte; Max Welling (NeurIPS, 2019)

Gradient $ ell_1$ Regularization for Quantization Robustness. - Milad Alizadeh; Arash Behboodi; Mart van Baalen; Christos Louizos; Tijmen Blankevoort; Max Welling (ICLR, 2020)

Up or Down? Adaptive Rounding for Post-Training Quantization. - Markus Nagel; Rana Ali Amjad; Mart van Baalen; Christos Louizos; Tijmen Blankevoort (ICML, 2020)

DIVA: Domain Invariant Variational Autoencoders. - Maximilian Ilse; Jakub M. Tomczak; Christos Louizos; Max Welling (MIDL, 2020)

Bayesian Bits: Unifying Quantization and Pruning. - Mart van Baalen; Christos Louizos; Markus Nagel; Rana Ali Amjad; Ying Wang 051; Tijmen Blankevoort; Max Welling (NeurIPS, 2020)

Gradient 𝓁1 Regularization for Quantization Robustness. - Milad Alizadeh; Arash Behboodi; Mart van Baalen; Christos Louizos; Tijmen Blankevoort; Max Welling (CoRR, 2020)

Federated Learning of User Authentication Models. - Hossein Hosseini; Sungrack Yun; Hyunsin Park; Christos Louizos; Joseph Soriaga; Max Welling (CoRR, 2020)

Improving Fair Predictions Using Variational Inference In Causal Models. - Rik Helwegen; Christos Louizos; Patrick Forré (CoRR, 2020)

Federated Learning of User Verification Models Without Sharing Embeddings. - Hossein Hosseini; Hyunsin Park; Sungrack Yun; Christos Louizos; Joseph Soriaga; Max Welling (ICML, 2021)

Federated Mixture of Experts. - Matthias Reisser; Christos Louizos; Efstratios Gavves; Max Welling (CoRR, 2021)

DP-REC: Private & Communication-Efficient Federated Learning. - Aleksei Triastcyn; Matthias Reisser; Christos Louizos (CoRR, 2021)

An Expectation-Maximization Perspective on Federated Learning. - Christos Louizos; Matthias Reisser; Joseph Soriaga; Max Welling (CoRR, 2021)

No time to waste: practical statistical contact tracing with few low-bit messages. - Rob Romijnders; Yuki M. Asano; Christos Louizos; Max Welling (AISTATS, 2023)

Hyperparameter Optimization through Neural Network Partitioning. - Bruno Mlodozeniec; Matthias Reisser; Christos Louizos (ICLR, 2023)

Federated Learning Toolkit with Voice-based User Verification Demo. - Prathamesh Mandke; Rachel Oberst; Matthias Reisser; Avijit Chakraborty; Christos Louizos; Joseph Soriaga; Daniel Madrigal Diaz; Andre Manoel; Nalin Singal; Jeff Omhover; Robert Sim (INTERSPEECH, 2023)

Quantization Robust Federated Learning for Efficient Inference on Heterogeneous Devices. - Kartik Gupta; Marios Fournarakis; Matthias Reisser; Christos Louizos; Markus Nagel (Trans. Mach. Learn. Res., 2023)

Protect Your Score: Contact-Tracing with Differential Privacy Guarantees. - Rob Romijnders; Christos Louizos; Yuki M. Asano; Max Welling (AAAI, 2024)

Importance Matching Lemma for Lossy Compression with Side Information. - Buu Phan; Ashish Khisti; Christos Louizos (AISTATS, 2024)

InterroGate: Learning to Share, Specialize, and Prune Representations for Multi-task Learning. - Babak Ehteshami Bejnordi; Gaurav Kumar; Amelie Royer; Christos Louizos; Tijmen Blankevoort; Mohsen Ghafoorian (BMVC, 2024)

A Mutual Information Perspective on Federated Contrastive Learning. - Christos Louizos; Matthias Reisser; Denis Korzhenkov (ICLR, 2024)

An Information Theoretic Perspective on Conformal Prediction. - Alvaro H. C. Correia; Fabio Valerio Massoli; Christos Louizos; Arash Behboodi (NeurIPS, 2024)

On Sampling Strategies for Spectral Model Sharding. - Denis Korzhenkov; Christos Louizos (NeurIPS, 2024)

DNA: Differentially private Neural Augmentation for contact tracing. - Rob Romijnders; Christos Louizos; Yuki M. Asano; Max Welling (CoRR, 2024)

Stable Diffusion-based Data Augmentation for Federated Learning with Non-IID Data. - Mahdi Morafah; Matthias Reisser; Bill Lin 001; Christos Louizos (CoRR, 2024)

Multi-Draft Speculative Sampling: Canonical Architectures and Theoretical Limits. - Ashish Khisti; MohammadReza Ebrahimi 002; Hassan Dbouk; Arash Behboodi; Roland Memisevic; Christos Louizos (CoRR, 2024)

Variational Learning ISTA. - Fabio Valerio Massoli; Christos Louizos; Arash Behboodi (Trans. Mach. Learn. Res., 2024)

Multi-Draft Speculative Sampling: Canonical Decomposition and Theoretical Limits. - Ashish J. Khisti; MohammadReza Ebrahimi 002; Hassan Dbouk; Arash Behboodi; Roland Memisevic; Christos Louizos (ICLR, 2025)

Approximating Full Conformal Prediction for Neural Network Regression with Gauss-Newton Influence. - Dharmesh Tailor; Alvaro H. C. Correia; Eric T. Nalisnick; Christos Louizos (ICLR, 2025)

Test-Time Adaptation with Source Based Auxiliary Tasks. - Motasem Alfarra; Alvaro H. C. Correia; Bernard Ghanem; Christos Louizos (Trans. Mach. Learn. Res., 2025)

Non-exchangeable Conformal Prediction with Optimal Transport: Tackling Distribution Shifts with Unlabeled Data. - Alvaro H. C. Correia; Christos Louizos (CoRR, 2025)