Louizos, Christos

29 publications

ICLR 2025 Approximating Full Conformal Prediction for Neural Network Regression with Gauss-Newton Influence Dharmesh Tailor, Alvaro Correia, Eric Nalisnick, Christos Louizos

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

NeurIPS 2025 Non-Exchangeable Conformal Prediction with Optimal Transport: Tackling Distribution Shift with Unlabeled Data Alvaro Correia, Christos Louizos

TMLR 2025 Test-Time Adaptation with Source Based Auxiliary Tasks Motasem Alfarra, Alvaro Correia, Bernard Ghanem, Christos Louizos

ICLR 2024 A Mutual Information Perspective on Federated Contrastive Learning Christos Louizos, Matthias Reisser, Denis Korzhenkov

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

ICLRW 2024 DNA: Differential Privacy Neural Augmentation for Contact Tracing Rob Romijnders, Christos Louizos, Yuki M Asano, Max Welling

AISTATS 2024 Importance Matching Lemma for Lossy Compression with Side Information Buu Phan, Ashish Khisti, Christos Louizos

ICMLW 2024 ImportanceWeighted Multi-Draft Speculative Sampling Ashish J Khisti, Arash Behravesh, Hassan Dbouk, Arash Behboodi, Roland Memisevic, Christos Louizos

NeurIPS 2024 On Sampling Strategies for Spectral Model Sharding Denis Korzhenkov, Christos Louizos

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

TMLR 2024 Variational Learning ISTA Fabio Valerio Massoli, Christos Louizos, Arash Behboodi

ICLR 2023 Hyperparameter Optimization Through Neural Network Partitioning Bruno Kacper Mlodozeniec, Matthias Reisser, Christos Louizos

AISTATS 2023 No Time to Waste: Practical Statistical Contact Tracing with Few Low-Bit Messages Rob Romijnders, Yuki M. Asano, Christos Louizos, Max Welling

TMLR 2023 Quantization Robust Federated Learning for Efficient Inference on Heterogeneous Devices Kartik Gupta, Marios Fournarakis, Matthias Reisser, Christos Louizos, Markus Nagel

NeurIPSW 2022 Decentralized Learning with Random Walks and Communication-Efficient Adaptive Optimization Aleksei Triastcyn, Matthias Reisser, Christos Louizos

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

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

ICLR 2020 Gradient $\ell_1$ Regularization for Quantization Robustness Milad Alizadeh, Arash Behboodi, Mart van Baalen, Christos Louizos, Tijmen Blankevoort, Max Welling

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

ICLRW 2019 DIVA: Domain Invariant Variational Autoencoder Maximilian Ilse, Jakub M. Tomczak, Christos Louizos, Max Welling

ICLR 2019 Relaxed Quantization for Discretized Neural Networks Christos Louizos, Matthias Reisser, Tijmen Blankevoort, Efstratios Gavves, Max Welling

NeurIPS 2019 The Functional Neural Process Christos Louizos, Xiahan Shi, Klamer Schutte, Max Welling

ICLR 2018 Learning Sparse Neural Networks Through L_0 Regularization Christos Louizos, Max Welling, Diederik P. Kingma

NeurIPS 2017 Bayesian Compression for Deep Learning Christos Louizos, Karen Ullrich, Max Welling

NeurIPS 2017 Causal Effect Inference with Deep Latent-Variable Models Christos Louizos, Uri Shalit, Joris M. Mooij, David Sontag, Richard Zemel, Max Welling

ICML 2017 Multiplicative Normalizing Flows for Variational Bayesian Neural Networks Christos Louizos, Max Welling

ICML 2016 Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors Christos Louizos, Max Welling

ICLR 2016 The Variational Fair Autoencoder Christos Louizos, Kevin Swersky, Yujia Li, Max Welling, Richard S. Zemel