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Christos Louizos

22 papers · 2016–2025 · 7 conferences · across top CS/AI conferences

Achievements

πŸ—ΊοΈ Taxonomy Completionist (12) 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird πŸƒ Academic Marathon (9) 🌍 Conference Polyglot (7) 🐝 Cross-Pollinator (11) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge 🀝 Dynamic Duo (13) πŸ‘‘ Triple Crown 🌱 Topic Pioneer πŸ† Grand Slam πŸ† Keyword Champion (2) πŸš€ Conference Pioneer ⚑ Prolific Year (5) πŸ”₯ Unstoppable (6) ❓ The Questioner πŸ“ˆ Trend Setter πŸ’Ž Century Club (22) πŸ—ƒοΈ Keyword Collector (92)

Conferences

ICLR (7) NIPS (6) ICML (4) AISTATS (2) AAAI (1) INTERSPEECH (1) MIDL (1)

Top co-authors

Max Welling (13) Tijmen Blankevoort (4) Matthias Reisser (4) Arash Behboodi (3) Mart van Baalen (3) Joseph Soriaga (2) Rob Romijnders (2) Yuki M. Asano (2) Rana Ali Amjad (2) Markus Nagel (2)

Research topics

Differential Privacy (1) Privacy (1)

Keywords

federated learning (4) model compression (4) variational inference (2) neural network quantization (2) bayesian inference (2) user verification (2) bayesian neural network (2) variational autoencoder (2) contact tracing (2) neural network (2) weight quantization (2) uncertainty estimation (2) causal inference (2) neural network pruning (2) sampling strategy (1) embedding learning (1) post-training quantization (1) domain generalization (1) distributed optimization (1) conformal prediction (1)

Papers

Multi-Draft Speculative Sampling: Canonical Decomposition and Theoretical Limits ICLR 2025
Approximating Full Conformal Prediction for Neural Network Regression with Gauss-Newton Influence ICLR 2025
On Sampling Strategies for Spectral Model Sharding NIPS 2024
An Information Theoretic Perspective on Conformal Prediction NIPS 2024
A Mutual Information Perspective on Federated Contrastive Learning ICLR 2024
Protect Your Score: Contact-Tracing with Differential Privacy Guarantees AAAI 2024
Importance Matching Lemma for Lossy Compression with Side Information AISTATS 2024
No time to waste: practical statistical contact tracing with few low-bit messages AISTATS 2023
Hyperparameter Optimization through Neural Network Partitioning ICLR 2023
Federated Learning Toolkit with Voice-based User Verification Demo INTERSPEECH 2023
Federated Learning of User Verification Models Without Sharing Embeddings ICML 2021
DIVA: Domain Invariant Variational Autoencoders MIDL 2020
Bayesian Bits: Unifying Quantization and Pruning NIPS 2020
Gradient $\ell_1$ Regularization for Quantization Robustness ICLR 2020
Up or Down? Adaptive Rounding for Post-Training Quantization ICML 2020
The Functional Neural Process NIPS 2019
Relaxed Quantization for Discretized Neural Networks ICLR 2019
Learning Sparse Neural Networks through L_0 Regularization ICLR 2018
Bayesian Compression for Deep Learning NIPS 2017
Multiplicative Normalizing Flows for Variational Bayesian Neural Networks ICML 2017
Causal Effect Inference with Deep Latent-Variable Models NIPS 2017
Structured and Efficient Variational Deep Learning with Matrix Gaussian Posteriors ICML 2016