Anian Ruoss | DeepAI

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∙ 09/19/2023

Language Modeling Is Compression

It has long been established that predictive models can be transformed i...

0 Grégoire Delétang, et al. ∙

∙ 05/26/2023

Randomized Positional Encodings Boost Length Generalization of Transformers

Transformers have impressive generalization capabilities on tasks with a...

0 Anian Ruoss, et al. ∙

∙ 02/06/2023

Memory-Based Meta-Learning on Non-Stationary Distributions

Memory-based meta-learning is a technique for approximating Bayes-optima...

0 Tim Genewein, et al. ∙

∙ 09/30/2022

Beyond Bayes-optimality: meta-learning what you know you don't know

Meta-training agents with memory has been shown to culminate in Bayes-op...

8 Jordi Grau-Moya, et al. ∙

∙ 07/05/2022

Neural Networks and the Chomsky Hierarchy

Reliable generalization lies at the heart of safe ML and AI. However, un...

3 Grégoire Delétang, et al. ∙

∙ 11/26/2021

Latent Space Smoothing for Individually Fair Representations

Fair representation learning encodes user data to ensure fairness and ut...

0 Momchil Peychev, et al. ∙

∙ 06/10/2021

Fair Normalizing Flows

Fair representation learning is an attractive approach that promises fai...

0 Mislav Balunović, et al. ∙

∙ 03/30/2021

Robustness Certification for Point Cloud Models

The use of deep 3D point cloud models in safety-critical applications, s...

0 Tobias Lorenz, et al. ∙

∙ 09/19/2020

Efficient Certification of Spatial Robustness

Recent work has exposed the vulnerability of computer vision models to s...

0 Anian Ruoss, et al. ∙

∙ 02/24/2020

Learning Certified Individually Fair Representations

To effectively enforce fairness constraints one needs to define an appro...

0 Anian Ruoss, et al. ∙

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