Aug 29, 2023 · In this paper, we propose of a novel framework generalizing these probabilistic reconstructions in the sense that it can handle other forms of ...
scholar.google.com › citations
Apr 3, 2024 · Our results suggest that optimal interpretable models are often more compact and leak less information regarding their training data than ...
Our results suggest that optimal interpretable models are often more compact and leak less information regarding their training data than greedily-built ones, ...
May 29, 2024 · In this paper, we propose of a novel framework generalizing these probabilistic reconstructions in the sense that it can handle other forms of ...
Duration: 15:38
Posted: Apr 9, 2024
Posted: Apr 9, 2024
Jun 14, 2024 · This paper presents a probabilistic approach for online dense reconstruction using a single monocular camera moving through the environment.
Aug 29, 2023 · 可解释性通常被认为是值得信赖的机器学习的关键要求。然而，学习和发布本质上可解释的模型会泄露有关底层训练数据的信息。由于此类披露可能直接与隐私发生 ...
Jun 17, 2024 · This paper introduces a novel theory of interpretable approximations, which aims to learn simple, interpretable models that can closely mimic the behavior of ...
Jul 15, 2024 · Scientific inference describes the process of rationally inducing knowledge about a phenomenon from such observational data (via ML, or other ...
Mar 17, 2022 · With the proposed model, we further design a recognition scheme based on the minimum reconstruction error criterion. Experiments on the measured ...